Journal of Intelligent & Fuzzy Systems - Volume 37, issue 5

Authors: Xiurong, Huang | Lei, Xiao | Xiaodong, Tou

Article Type: Research Article

Abstract: Due to the large amount of pollutant discharge, the environmental pollution capacity of the coastal waters of the Yellow Sea and Bohai Sea in China is seriously overloaded, which has caused unacceptable impact on the marine ecological environment. Based on this, this paper is based on the cloud computing model of marine environmental management scientific decision-making evaluation algorithm, constructing a model of complex network dynamic correlation characteristics, and externally describing water bloom. Through the weight parameters in the cloud model, it is effectively applied to the evaluation of marine environmental management science decision support system. According to the complexity characteristics …of cyanobacterial bloom management decision, the cyanobacteria bloom control decision model is inferred, and the intuitionistic fuzzy rough set algorithm is improved. The similarity is calculated, the best matching case is found, and the experts are adjusting to form a governance plan. The research results show that the scientific decision-making evaluation algorithm of marine environment management based on cloud computing model is effective for the verification of marine environmental management science decision support system evaluation system, embedding eutrophication evaluation method and cyanobacteria water bloom governance decision-making method into water quality remote monitoring and cyanobacteria water China’s governance decision-making system, to achieve the decision-making of cyanobacteria bloom control in the lake water body. Show more

Keywords: Cloud computing, ocean, environmental management, scientific decision

DOI: 10.3233/JIFS-179169

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5877-5886, 2019

Authors: Li, Xiaoqin

Article Type: Research Article

Abstract: With the development of the Internet, the application of multimedia in College English teaching is becoming more and more demanding, especially in the area of accurate information recommendation. In order to improve the accuracy of push information in College English multimedia teaching broadcasting, a particle swarm optimization (PSO) algorithm is proposed in this paper. By designing a massless particle to simulate the foraging behavior of birds, the algorithm searches for precise targets to obtain the optimal solution. Combining with Internet technology, the weight of data transmitted by multimedia broadcasting signal is calculated by setting an independent address, and then the …interactive data flow between teachers and students is analyzed to optimize the design of multimedia broadcasting terminal. The results show that the indicators with higher scores are mainly distributed in the construction of network teaching platform. The three indicators with the highest scores are convenience, module integrity and management and maintenance, which are 2.825, 2.715 and 2.696, respectively. Through this study, it brings new inspiration to the intellectualization of College English teaching. Multimedia broadcasting design can solve the problem of interference in terminal broadcasting transmission by setting independent addresses. Show more

Keywords: College English teaching, multimedia, broadcasting, terminal design, internet

DOI: 10.3233/JIFS-179170

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5887-5895, 2019

Authors: Liu, Minghui | Xiang, Zheng

Article Type: Research Article

Abstract: In this paper, a novel signal candidate generation method and a new joint coding and probability peak to average power ratio (PAPR) reduction scheme are proposed for a Luby transform (LT) coded orthogonal frequency division multiplexing (OFDM) system. When a few LT packets are mapped into an OFDM symbol, all subcarriers are automatically divided into several blocks. We permutate these packets and assign them different subcarrier blocks to generate different signal candidates instead of multiplying by many phase rotation vectors and using active constellation extension, and the transmitted symbol will be the one whose PAPR is the smallest. Moreover, through …introducing one phase rotation vector, the proposed algorithm is modified, and the PAPR reduction performance is enhanced. Simulation results prove that our proposed scheme can not only fully explore the spatial freedom brought by the mapping relationship between LT packets and OFDM symbols but also can obtain effective PAPR reduction performance. Since the permutation operation does not change the degree value of each packet, the new scheme can still maintain good decoding performance. Show more

Keywords: PAPR reduction, OFDM, luby transform

DOI: 10.3233/JIFS-179171

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5897-5904, 2019

Authors: Yan, Liu

Article Type: Research Article

Abstract: Music education plays a particularly important role in China’s existing education systems at all levels. With the development of Internet of Things (IoT) technology, interactive teaching methods are more and more widely used. Therefore, a piano teaching system model design algorithm is proposed based on the IoT technology to design the function of the piano teaching system, which is of great help to improve the quality of piano teaching. The current mature technical framework and development language are compared, the key technologies of the IoT using the system architecture is determined, and the structural design methods of the piano teaching …system analyzed, mainly using the SSH framework (ie Stmts, Spring and Hibernate’s model, based on this paper, a model design algorithm is proposed for building a piano teaching system based on the IoT technology. Finally, the algorithm and system are tested and implemented through experiments. The research results show that the algorithm uses the hardware underlying direct control development method, with an average scan of 12 times in 0.3 s, the recognition probability can be increased to 0.999719, the algorithm is effective, and the designed piano teaching system is fully functional. The research in this paper provides a theoretical reference for the wide application of IoT technology and the optimal design of piano teaching system. Show more

Keywords: IoT, piano, teaching system, SSH

DOI: 10.3233/JIFS-179172

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5905-5913, 2019

Authors: Yao, Lu

Article Type: Research Article

Abstract: With the introduction of the information age, enterprise financial management has been challenged as never before, and the application of Internet of Things (IoT) technology can effectively improve the efficiency of financial accounting management and realize the informationization of financial management. In order to solve the problem of enterprise financial accounting data processing, a data mining algorithm is constructed, which uses data mining technology to obtain massive information data and cluster analysis processing to realize the fusion of multiple uncertainty information processing models. Firstly, the financial information cloud platform is designed by using the IoT technology. The financial risk index …coefficient of the enterprise is judged by the association rules. Finally, the research sample is divided into the risk group and the normal group according to the ST classification standard, and the 296 financial indicators of the two groups are correlated. The research results show that if the enterprise with a score below 40 points has financial risk, the accuracy rate is 70.9%, which is slightly lower than the financial risk warning model of the decision tree. Through the research of this paper, it has enlightenment to the financial accounting management of IoT enterprises. The data mining technology is applied in the processing of massive data information of accounting, which is moreefficient. Show more

Keywords: data mining algorithm, enterprise, financial accounting, smart management

DOI: 10.3233/JIFS-179173

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5915-5923, 2019

Authors: Qi, Bo

Article Type: Research Article

Abstract: The emergence of resource conflicts and overload control problems during the playback of smart TV terminals has brought many obstacles to the operation of smart TV terminals, which has seriously affected the user experience of smart TV terminal users. In this regard, the adaptive media playback algorithm is optimized for smart TV terminals. This method performs dynamic priority preemptive scheduling on exclusive resources according to resource characteristics and application priorities to optimize resource allocation and improve media playback. The feedback control algorithm is used to perform QoS scheduling on shared resources until QoS proportional fairness is achieved, and QoS proportional …compression is used to eliminate resource overload. Finally, a DASH server on Apache and implements an analog DASH client using Python are built. In order to verify the performance of the algorithm, the research results show that the adaptive media playback algorithm has the overload control capability, which only solves the resource conflict and improves the response performance under heavy load of the system, and the algorithm consumes only 4.5% of the overall system QoS. Compared with the existing methods, it is about 30% lower, which is more suitable for resource scheduling of smart TV terminals. The research in this paper shows that the adoption of QoS scheduling mechanism contributes to the optimization of media playback resources and allocation ratio, thus making the playback process of smart TV terminals, which provides a reference for the optimization of smart TV terminal playback. Show more

Keywords: Smart TV, terminal, media playback, algorithm optimization

DOI: 10.3233/JIFS-179174

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5925-5934, 2019

Authors: Ren, Xiaojian

Article Type: Research Article

Abstract: The research technique of human motor nerve is more complicated. In order to improve the understanding level of human motor nerve structure, a fusion architecture of human motion nerve and neural network computer driven by education are proposed. The human motor nerve simulation model is established by using the computer data simulation model. The model proposes an optimization scheme from the algorithm flow, the data transformation technology used to improve the real-time performance of the neural network and enhance the dynamic capture of the motor nerve changes. In order to further improve the architecture of the neural network and computer …architecture driven by sports, a neural network algorithm is added to realize the sequence optimization of data to test the authenticity and efficiency of the human neural network simulation model neural network algorithm. In this paper, the feasibility and functionality of the algorithm are tested with comparative experiments. The results show that the neural network algorithm neural network algorithm not only has a calculation time of only 12 seconds. Moreover, the calculation accuracy is high, achieving a high level of accuracy of 98%. On the other hand, other algorithms have lower accuracy and longer calculation time. The research shows that the neural network algorithm can improve the human motor nerve capture and optimize the architecture, which can provide reference for the fusion of human motion nerve and computer technology in the future. Show more

Keywords: Sports drive, motion nerve, neural network algorithm, structure fusion

DOI: 10.3233/JIFS-179175

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5935-5943, 2019

Authors: Yunxing, Wang

Article Type: Research Article

Abstract: In a certain network environment, the use of teaching evaluation assistant decision-making system can further promote the rationality and fairness of teaching evaluation. Two screening algorithms are proposed, which combine with the influence factors in the automatic evaluation model of physical education teaching, delete the relevant factors and leave them behind. After two deep screening, the accuracy of the results is improved. By introducing the artificial neural network technology into the evaluation of physical education teachers’ teaching quality, the evaluation factors of neurons are calculated to establish the evaluation model of BP neural network. Secondly, the factors affecting the evaluation …results in the evaluation model of BP neural network are decomposed and screened by using the second screening method, and a certain amount of training and learning is carried out for the teaching quality data. The experimental results show that the second screening algorithm is effective and can improve the accuracy of the results of automatic evaluation of physical education teaching. By establishing the automatic evaluation model of physical education teaching, it can provide reference for the evaluation and assistant decision-making of physical education teaching quality in Vocational colleges. Show more

Keywords: Twice screening algorithm, physical education teaching, automatic evaluation

DOI: 10.3233/JIFS-179176

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5945-5953, 2019

Authors: Wang, Han

Article Type: Research Article

Abstract: With the improvement of people’s living standards, people’s pursuit of material and high quality of living environment must combine the concept of human and nature to integrate urban landscape design with the surrounding ecological environment. The most interesting thing is the landscape design of most coastal cities. Based on this, a virtual environment is proposed based on virtual reality technology and intelligent algorithm, using 3-bit binary to represent the digital factor and creating the virtual environment by simulating the display environment. After constructing the basic model of coastal landscape, the landscape design of coastal areas using virtual reality technology is …analyzed, and the parametric design method of new images in landscape design analyzed, the landscape design of virtual reality technology in coastal areas analyzed. The research results show that the display degree of DEM is 50% and the image display detail degree is 90% by using virtual reality technology. Combined with 3DMAX, it can be transferred to the 3DMAX operation surface to perform real editing and simulation of the coastal garden environment. Thus, the algorithm proposed in this paper is effective. The research in this paper shows that it is feasible to apply virtual reality technology and intelligent algorithm to landscape design in coastal areas, and has achieved certain effects. Show more

Keywords: Virtual reality technology, intelligent algorithm, coastal area, landscape design

DOI: 10.3233/JIFS-179177

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5955-5963, 2019

Authors: Yipu, Wang

Article Type: Research Article

Abstract: At present, in the context of the Internet of Things (IoT), more and more teaching institutions have integrated Internet technology into the English network teaching system. Therefore, based on the IoT technology, an English speech recognition algorithm is proposed based on the network teaching system, and develops the function of the network teaching system oriented to English speech intonation. In this paper, the function of the platform and the design of the key modules of the system are proposed in detail. During the operation of the recognition model, the collected speech signals are preprocessed, effective speech feature parameters are extracted, …and each frame feature parameter is composed into a vector sequence. The different sequences are classified, and the speech intonation system is developed based on the classification results. Then the improved particle filter algorithm is used to further improve the accuracy and speed of English speech system recognition, and the function of English speech network teaching system is optimized based on this. Experiments show that the excerpts from the China Daily website in the system of this article, most of them can be spliced with word primitives, reaching more than 90% of the total number of words in the measured text, reflecting the system’s higher word and segment coverage and high accuracy. The research in this paper has certain theoretical reference value for the construction and optimization of English phonetic system and the further development and use of IoT technology. Show more

Keywords: IoT, English phonetic intonation, network teaching system, function, development

DOI: 10.3233/JIFS-179178

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5965-5972, 2019

Authors: Wu, Weiqun | Yin, Bin

Article Type: Research Article

Abstract: The recommendation system is an important means to solve the “information overload” of e-commerce today. Consumer psychology believes that consumer psychology dominates consumer behavior, and consumer behavior is the external manifestation of consumer psychology. Therefore, the personalized recommendation algorithm of user consumption psychology is studied based on the specific perspective of local group-buying e-commerce. By constructing a user social relationship network, the personalized recommendation algorithm is evaluated and the final recommendation result is obtained. A personalized recommendation model is proposed based on multi-dimensional space, which is compared with the existing personalized recommendation model. The simulation results show that the improved …collaborative filtering recommendation method has a large recall rate and accuracy during the daytime. And F value; when the number of recommended results is small at night, the traditional recommendation method has a slightly larger recall rate, accuracy rate and F value, but as the number of recommended results increases, the recommended effects decrease. In general, the proposed method of the recommended algorithm has a good effect. The method proposed in this paper can improve the accuracy of recommendation and partially eliminate the cold start problem of users, which has certain enlightenment for the expansion of personalized recommendation algorithm and the improvement of e-commerce user management. Show more

Keywords: Group purchase, e-commerce users, consumer psychology

DOI: 10.3233/JIFS-179179

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5973-5981, 2019

Authors: Linlin, Yang | Song, Zhang

Article Type: Research Article

Abstract: The development of English teaching mode and students’ speculative ability training mode is slow. In order to improve the quality of English teaching and improve students’ speculative ability, the English teaching mode and the cultivation of students’ speculative ability based on Internet of Things (IoT) are proposed and typical cases are analyzed. The computer data simulation model is used to construct an English teaching innovation model. The model proposes an optimization scheme from the algorithm flow, and uses the data transformation technology to improve the real-time teaching and strengthen the efficiency of teaching management. In order to further improve the …students’ speculative ability in English teaching, the particle swarm optimization algorithm is added to the model to realize the sequence optimization of the data, and the authenticity and efficiency of the particle swarm optimization algorithm in the English teaching model are verified. The test results show that the particle swarm algorithm can self-improve and repair functions, continuously improve the accuracy of the English teaching model, and optimize the teaching method. The research shows that the particle swarm optimization algorithm can improve the quality of English teaching and optimize the architecture, which can provide reference for the future integration of English teaching and computer technology. Show more

Keywords: English teaching, IoT, particle swarm optimization, speculative ability

DOI: 10.3233/JIFS-179180

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5983-5991, 2019

Authors: Runzhao, Yang | Qianni, Cao

Article Type: Research Article

Abstract: With the increasing number of electric vehicles, the location problem of charging stations has been paid more and more attention. It is more efficient and scientific to select electric vehicle charging stations through intelligent algorithms. Aiming at the location selection of electric vehicle charging station based on time satisfaction, a bi-level planning model is constructed for electric vehicle charging station location, and introduces genetic algorithm into the model to scientifically calculate the location of charging station. The candidate data string is extracted by genetic algorithm, and the text candidate string and the image candidate string are obtained. The candidate string …is used as the document attribute to construct the electric vehicle charging station location plan, and then the ideal charging station address is solved. Finally, the method is applied. It is used in the planning analysis of the area near Chaowai Street in Chaoyang District, Beijing. The research results show that the six charging points calculated by the method can meet the demand of the charging vehicles of the residents in the planned area, which is in line with the actual situation of the planned area. This also shows that the double-layer planning model is used for site selection. The research in this paper shows that the genetic algorithm can be effectively used in the location problem, which can improve the efficiency of work and the accuracy of site selection. The relevant conclusions can provide a theoretical reference for the development of site selection. Show more

Keywords: Computer, genetic algorithm, electric car, charging station location

DOI: 10.3233/JIFS-179181

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5993-6001, 2019

Authors: Zhu, Zhang | Tian, Han | Xiaoyang, Yu

Article Type: Research Article

Abstract: The transmission of ECG signal is a key technology of wireless body area network technology center. An ECG emotion classification algorithm based on body area network is proposed. In this method, SV vector function is used to fit ECG signals, and the fitting parameters are obtained. After estimating the channel characteristics, the fixed-point parameters are transmitted. Firstly, the wireless body area network technology is analyzed, because the body area network can deal with long-distance dependence and capture the semantic information of input text. Wireless body area network is used to extract the grammatical features of input text. Then, based on …the wireless field of network technology, the principle of support vector machine (SVM) is proposed. On the basis of the emotion classification model, an algorithm based on speech recognition is constructed, and the input text vector obtained by CNN is used to represent the emotion category of the output layer. Finally, the experimental results show that the algorithm is effective, and the emotional classification model can obtain the highest accuracy in multiple data sets. The results show that the algorithm can not only fit the waveform of ECG emotional signals well, reduce the compression ratio and achieve a certain fitting effect, but also improve the detection and transmission ability of ECG (emotional) ECG signals. Show more

Keywords: Body area network, ECG, emotion classification algorithm

DOI: 10.3233/JIFS-179182

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6003-6011, 2019

Authors: Yi, Zhong

Article Type: Research Article

Abstract: With the rapid development of the IoT, the traditional traffic scheduling optimization model is difficult to adapt to the development needs of emerging services, bringing new challenges and problems to data center management. In order to solve the problem of data traffic management in data center network, a clustering algorithm is constructed to analyze its key technologies. The algorithm divides the data to be observed into a certain number of “class clusters” by some predetermined features, so that the similarity of the data in the cluster is measured by a certain “distance function” within each “class cluster". By analyzing the …RFID automatic radio frequency identification technology, a data classification model based on RFID automatic radio frequency identification technology is constructed. The original data of the unbalanced state is processed based on the hierarchical partitioning method, and the sampling data analysis result is obtained. The results of data training experiments on the model show that for the prediction of a few samples, the prediction of the unbalanced data set has been further improved, and the AUC value has reached 98.72%. Research has provided new ideas for the operation and management of data centers. Show more

Keywords: RFID automatic radio frequency identification technology, data center, algorithm optimization

DOI: 10.3233/JIFS-179183

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6013-6020, 2019

Authors: Hua, Tao | Li, Laixiang

Article Type: Research Article

Abstract: With the rapid development of the Internet, the use of computer networks is becoming more and more frequent. However, in the process of network use, various vulnerabilities and some other factors lead to network security problems occur from time to time. How to make the network provide efficient and rapid services for people and also meet different levels of security issues has become a problem. Based on this, the use of artificial intelligence technology has been studied, and the system detection algorithm based on the concept of artificial intelligence has been proposed. Integrating artificial intelligence into the field of network …security can not only improve the overall performance of the network, but also effectively and reliably guarantee the security. Firstly, according to the characteristics of computer network system, an immune detection algorithm is proposed to evaluate the security of the system. Secondly, based on the analysis of computer network security technology, a system detection algorithm based on artificial intelligence concept is further proposed. Then, data mining is carried out based on Prefix, and the intrusion lines and their correlation are analyzed. Finally, the effectiveness of the algorithm is analyzed experimentally. The results show that the proposed algorithm has good accuracy and adaptability, and can play a good supporting role in the security detection of computer network system. Show more

Keywords: Artificial intelligence, computer network, security technology

DOI: 10.3233/JIFS-179184

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6021-6028, 2019

Authors: Ai, Yi | Pan, Weijun | Yang, Changqi | Wu, Dingjie | Tang, Jiahao

Article Type: Research Article

Abstract:  Along with the rapid increasement of flights and projects of extending and building airports, the probability of flight delays is also increasing. People begin to pay more attention to the prediction of flight delays in a large civil aviation air traffic network. In this paper, we employ a deep learning (DL) model— the convolutional long short-term memory network (conv-LSTM), to address the airport delay prediction in network structure. The spatiotemporal variables including flight delays of airport, air route congestion, airport throughput and flow control are input into an end-to-end learning architecture as a spatiotemporal sequence. The future flight delays in …airport will be output by the model. Experiments show that conv-LSTM possess stronger ability to capture temporal and spatial characteristic than traditional LSTM. Show more

Keywords: Flight delay, civil aviation air traffic network, spatiotemporal distribution prediction, deep learning, convolutional long short-term memory network (conv-LSTM)

DOI: 10.3233/JIFS-179185

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6029-6037, 2019

Authors: Shi, Yongqiang | Liu, Zheng | Chen, Li | Li, Wei

Article Type: Research Article

Abstract: With the development of China’s Internet, wireless network technology has been upgraded, and the rapid development of wireless network technology requires more advanced intelligent information processing technology to match. Therefore, based on the development of wireless network, this paper proposes intelligent tourism Management scheme. Firstly, the Wide & Deep Learning exploratory tourism route recommendation model was constructed. Then the Wide & DSSM exploratory recommendation algorithm combining the traditional recommendation algorithm with the depth model was proposed. Finally, the model and algorithm were tested through experiments. In this paper, the algorithm was used to study the semantic space vectors of both …the user dimension and the Travel line dimension, and the data of the user dimension was fully utilized, which brought a significant improvement to the performance of the recommended system. Show more

Keywords: Wireless network, intelligent tourism, recommendation, tour route

DOI: 10.3233/JIFS-179186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6039-6046, 2019

Authors: Ju, Luansheng

Article Type: Research Article

Abstract: In the performance of vocal music, the human body noise science is a problem that cannot be ignored. The wrong pronunciation often causes noise diseases. It is necessary to analyze the localization of vocal noise. Based on this article, the research of vocal art performance and human noise science based on wireless sensor system is studied. At first, this article briefly describes the relationship between vocal art performance and human noise, and then puts forward the importance of noise localization. Aiming at the problem of noise localization, several target localization algorithms are proposed. At the same time, these algorithms are …weighted to reduce the complexity and improve the calculation accuracy. The simulation results test confirmed the effectiveness of the target location weighting algorithm without increasing the computational complexity, and the calculation accuracy was significantly improved. Show more

Keywords: Vocal art, human body noise, wireless sensor, noise location

DOI: 10.3233/JIFS-179187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6047-6054, 2019

Authors: Yang, Ning

Article Type: Research Article

Abstract: The construction of the artificial translation scoring model based on BP neural network has a positive effect on the improvement of college students’ translation performance. In order to promote the application of this kind of system in English teaching in our country, in this study, the author summarized the subjective topic scores in English teaching in our country, and then the author constructed the artificial translation scoring model of BP neural network. Compared with the example application, the comparison results show that the artificial translation scoring system based on BP neural network is more effective than the traditional scoring method. …This study aims to provide reference for the continuous improvement and development of our English language teaching model. Show more

Keywords: Translation, scoring system, BP neural network, artificial translation scoring model

DOI: 10.3233/JIFS-179188

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6055-6062, 2019

Authors: Xia, Chenhong

Article Type: Research Article

Abstract: There is a certain correlation between human health and actual exercise. This has always been one of the focuses of many scholars. When analyzing the movement of human body, a lot of modern technology and equipment need to be used. In order to better realize the physical health of young people in our country, the health service system based on sensor technology has been put forward. By introducing accelerometer technology, real-time data capture and analysis of human motion posture and movement trajectory were carried out. At the same time, the reliability of the algorithm was improved. In order to verify …the feasibility of the method, a practical case was verified. Experimental results showed that the method was more scientific and reasonable in motion capture analysis. Show more

Keywords: Sensor technology, motion index, health system

DOI: 10.3233/JIFS-179189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6063-6069, 2019

Authors: Zhu, Xianwen

Article Type: Research Article

Abstract: At this stage, the rapid development of computer technology and information technology in China has provided favorable conditions for the development of the game. In order to pursue the game experience, how to use artificial intelligence in the game has become a new research hotspot. Therefore, the current situation of artificial intelligence used in games was investigated, and the principles of Unity3D game engine were studied; then the intelligent behavior model for NPC was established by using the behavior tree as the basic algorithm, and the AI architecture of the agent in the game was designed; moreover, combined with the …above analysis, the behavior tree model based on Q learning algorithm was calculated, and the application of Unity3D in the game was completed; finally, a game model was developed in combination with Unity3D game engine. The results show that the behavior tree based on Unity3D game engine can realize NPC’s intelligent behavior simply and efficiently, and the system can run at a good speed, which has theoretical guidance for the follow-up research of game artificial intelligence and simulation training. Show more

Keywords: Unity3D, intelligent behavior, behavior tree, non-player character (NPC)

DOI: 10.3233/JIFS-179190

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6071-6079, 2019

Authors: Li, Xiaohong | Li, Maolin

Article Type: Research Article

Abstract: Traditional information recommendation system using only the user’s score is calculated and recommended, although to a certain extent, can obtain the implied characteristics of users or resources, but the lack of enough semantic interpretation, affecting the effects of recommendation. This article studied and analyzed the recommendation based on attribute coupled matrix decomposition algorithm in the application of Internet of things, on the foundation of the matrix decomposition model successively introduced global offset and time offset, in order to improve the prediction accuracy and the quality is recommended. In this paper, the algorithm is proved by experiment and the prediction accuracy …of the algorithm is improved. Show more

Keywords: Property coupling, matrix decomposition, recommendation algorithm, internet of things

DOI: 10.3233/JIFS-179192

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6081-6089, 2019

Authors: Wang, Bin | Dai, Jing

Article Type: Research Article

Abstract: With the continuous improvement of the social and economic level, the investment in fixed assets in the whole society is increasing steadily, while the phenomenon of uncontrollable investment is becoming more and more serious. Therefore, it is very important to increase the investment estimate in the early stage of the project construction. Based on this, in this paper, by studying the BP neural network, a mathematical model of the prediction of engineering cost based on the improved BP neural network model was proposed; then, taking a 15-storey tall building in a residential district as a prediction object, by collecting and …sorting out engineering cost data similar to the predicted object, the improved BP neural network model was estimated and trained; finally, the prediction of the engineering cost data for the project was carried out, and the actual results were compared with the estimation results of the traditional prediction model; thus, the speediness and accuracy of the proposed improved BP neural network model in the field of the prediction of engineering cost were verified. Show more

Keywords: BP neural network, improved BP algorithm, engineering cost, prediction model

DOI: 10.3233/JIFS-179193

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6091-6098, 2019

Authors: Zhang, Ming

Article Type: Research Article

Abstract: With the rapid development of wireless networks, the issue of information security in wireless communications has gradually emerged, and it has become one of the biggest obstacles to the popularization of this technology. To meet the increasing security and reliability requirements of new network environments, wireless network security standards and protocols are constantly being updated and enhanced. Based on the current development of wireless networks in Beijing, this paper discusses the optimization of encryption protocols in network security protocols, introduces the PrefixSpan algorithm and improves its algorithms, and then performs data mining based on Prefix, and analyzes the intrusion lines …and their correlations. Finally, the feasibility of using the improved PrefixSpan algorithm to optimize the encryption protocol is verified through experiments. Show more

Keywords: Prefixspan algorithm, data mining, network security, encryption protocol

DOI: 10.3233/JIFS-179194

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6099-6106, 2019

Authors: Tan, Lingling | Li, Qian

Article Type: Research Article

Abstract: With the popularity of computer technology, big data, Internet of things and other new IT technologies appear. With the rapid transformation of the times, the traditional logistics industry can no longer meet the needs. Therefore, the new logistics method has been studied by various technicians. Petri network logistics is one of the new methods. The knowledge flow modeling of supply chain under Petri network is expounded. The basic theory and method of logistics are analyzed. Using the particle swarm optimization (PSO) algorithm of data Petri network to combine the Internet of things with Petri network, the innovation research is carried …out and the supply chain knowledge flow model is built. In the test of information operation efficiency of the algorithm, it is proved that our algorithm is feasible. Show more

Keywords: Petri network, logistics, supply chain knowledge flow

DOI: 10.3233/JIFS-179195

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6107-6114, 2019

Authors: Li, Jiangbo | Wang, Yumin

Article Type: Research Article

Abstract: Industrial cluster is a common phenomenon in the process of industrialization. It is an external scale formed by agglomeration effect. Cluster enterprises based on their comparative advantages, innovation will be in the system innovation, management innovation, technological innovation, corporate culture innovation and other all-round development. The empirical results show that the development of industrial clusters attracts and promotes a large number of intermediary service-oriented organizations, as well as institutions providing research and development and technical support, providing innovative incubation platform. The diffusion behavior of technological innovation of enterprises in clusters plays an important role in upgrading industrial clusters, but uncontrolled …imitation behavior will reduce the expected profits of enterprises taking the lead in innovation and increase innovation risks. At the same time, the supporting innovation service system integrates and improves the factors gathering and optimization needed for innovation, and provides a technological support platform for enterprises in clusters to innovate.Therefore, the government’s policy should be biased towards establishing an effective mechanism for the interaction between scientific and technological innovation and industrial clusters, so as to achieve a good situation of the interaction between economy and science and technology. Show more

Keywords: Fuzzy model, industrial cluster, technological innovation, complex network

DOI: 10.3233/JIFS-179196

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6115-6126, 2019

Authors: Yansong, Liu | Li, Zhu | Feng, Liu

Article Type: Research Article

Abstract: The security of massive data has always been the focus of computer security research. With the increase of data storage, the computing platform of single node can not deal with the increasing security of massive data. It is urgent to use distributed computing platform to improve computing efficiency and detection accuracy. The physical deployment of intrusion detection system on cloud computing platform consists of monitoring server, Hadoop master server, IDS server, node and IDS terminal management. The experimental results show that the proposed intrusion detection system based on Hadoop cloud node has better detection effect. This paper searches for the …optimal weights, and then begins the training of the neural network. The whole process uses the Hadoop framework of distributed computing platform to implement the genetic algorithm and the neural network algorithm in the cloud computing platform. At the same time, the algorithm is improved to improve the efficiency and accuracy of intrusion detection. The results show that the intrusion detection technology is very effective to protect the application system and help it against various types of intrusion attacks. Show more

Keywords: Intrusion detection algorithms, cloud computing, distributed networks, detection rate

DOI: 10.3233/JIFS-179197

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6127-6138, 2019

Authors: Chen, Gang

Article Type: Research Article

Abstract: The effective supply guarantee of fresh agricultural products is a systematic problem. Farmers should not only pursue economic effectiveness, but also ensure the quality of products. This paper analyzes the supply decision of agricultural products based on negative exponential utility function and game analysis. The negative exponential utility function has been widely used in the study of the risk preferences of farmers. This paper analyses the impact of price fluctuation on the supply of agricultural products. At the same time, it analyses the problem of quality and safety from the perspective of the main body of agricultural products supply under …the framework of economics. The income of agricultural products is an important factor affecting their behavioral decision-making. The result shows that: (1) price affects utility values by affecting the profit values and the mean risk-aversion coefficients; (2) market competition gives producers and operators inherent motivation to improve the quality of agricultural products. In the process of production decision-making, it is necessary to ensure that the profit of supplying safe agricultural products is not less than that of supplying conventional agricultural products. Therefore, the government can adopt economic incentive and policy incentive mechanism to protect the economic interests of the main body of safe agricultural products supply. Show more

Keywords: Utility function, optimal decision, supply chain network, quality of agricultural products

DOI: 10.3233/JIFS-179198

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6139-6149, 2019

Authors: Yu, Wang | Huafeng, Wang

Article Type: Research Article

Abstract: Extreme value theory can analyze the extreme changes of financial market returns, and it is an effective financial risk management model. The distribution characteristics of financial assets’ returns are the core content of all financial models. The assumptions about the fluctuation behavior of returns and its distribution characteristics are of great theoretical and practical significance for the measurement and management of financial risks. We compare the estimates of value at risk by the peak over threshold model with that by the traditional variance-covariance method. During downturns, the peak over threshold model based value at risk estimates is higher relative to …that by the traditional variance-covariance approach. At the same time, this paper conducts statistical analysis of basic data through data collection and combines the establishment of statistical methods to study the practical effects of various factors on carbon productivity in China. In addition, this paper constructs a low-carbon economic neural network model based on particle swarm optimization to study carbon emissions. Finally, on the basis of analysis and research, this paper puts forward policy recommendations for China’s future low-carbon development model, and then provides reference for guiding the development of China’s future low-carbon model and provides theoretical basis for subsequent related research. Show more

Keywords: Particle swarm optimization, multidimensional analysis, neural network, financial risk

DOI: 10.3233/IFS-179199

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6151-6163, 2019

Authors: Kong, Fei | Wang, Yumin

Article Type: Research Article

Abstract: At present, there is less software related to sport technical behavior recognition, and there are few studies on the classification and identification of detailed actions. By introducing computer technology to analyze the efficiency and regularity of sports, not only the characteristics of athletes can be excavated, but also the visibility and dynamic tracking of sport training can be provided. The process of sports education is a fast and complex systematic process. Through the interactive system of physical education, we can use different methods to collect sports data and make a comparative analysis of athletes’ movements. Through the data mining of …the relationship between athletes’ physiological indexes and sports load, the unreasonable link in sports training can be avoided. Also, in sports training, we can use computer vision and modern biomechanics to construct a virtual sports education situation. With the classification accuracy as the fitness function, this paper collects the data through the network database, and returns the corresponding sport training parameters on this basis. The results showed that the accuracy of the model was nearly 98%, which met the actual demand. Therefore, the development of sports education assistant system can provide strong support for the process control of sports training and education. Show more

Keywords: Support vector, improved model, computer interactive system, recognition algorithm

DOI: 10.3233/JIFS-179200

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6165-6175, 2019

Authors: Bo, Wang | Tianyu, Fan | Zhiyong, Li | Xiangtian, Nie

Article Type: Research Article

Abstract: There is little research on the relationship between financial innovation and economic growth, and the research on the synergy between the two is basically blank. Based on this, from a general perspective, through constructing the corresponding subsystems in combination with financial innovation and economic growth, establishing the corresponding synergy model, and discovering the synergy development relationship by studying the degree of synergy in the past period, this study builds a BP neural network simulation model to predict the degree of synergy between financial innovation and economic growth in 2018 on the basis of practice. At the same time, this study …compares it with the actual situation to verify its effectiveness. Through analysis, the research model has certain effectiveness, which is basically consistent with the actual development trend. The research proposes that the main trend of financial innovation from the perspective of generalized virtual economy is Internet finance. This is the first time to study this issue from a new perspective, theory and method, which expands the existing research results. Show more

Keywords: BP neural network, financial innovation, economic growth, synergy

DOI: 10.3233/JIFS-179201

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6177-6189, 2019

Authors: Li, Tuojian | Sun, Jinhai | Zhang, Xianliang | Wang, Lei | Zhu, Penglei | Wang, Ning

Article Type: Research Article

Abstract: Competitive sports require athletes to operate in real time, and there are many uncertainties. At present, there are few applications of artificial intelligence in the prediction of competitive sports, and the relevant literature about fitness motivation is rare. Based on this, this study is based on the machine learning algorithm and uses the support vector machine to build the competitive sports model and fitness motivation evaluation. At the same time, this study combines the actual situation to construct a corresponding factor analysis model for racing sports, and this factor analysis is a combination of data mining and machine learning. Only …by adopting appropriate measures can students’ motivation of physical fitness be effectively fostered and stimulated, their active participation in physical exercise and lifelong fitness habits be fostered. On the basis of traditional SVM method, PCA-SVM model is constructed to further improve the prediction accuracy and validity of fitness motivation. In this paper, the principal components of eight kinds of operation behavior are extracted; fitness motivation is not only the direct reason for college students to participate in fitness exercise, but also the motive force of fitness behavior. Grid Search algorithm is selected to optimize the parameters of SVM. The recognition rate of Grid Search-SVM is 94.79%, and satisfactory results are obtained. Show more

Keywords: Support vector machine, racing sports, regression model, GA-SVM algorithm

DOI: 10.3233/JIFS-179202

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6191-6203, 2019

Authors: Guangjing, Li | Cuiping, Zhang

Article Type: Research Article

Abstract: At present, artificial intelligence for sports static image recognition is mostly in the action judgment stage, but less analysis on the action detail stage. Based on this, based on machine learning, this study uses static images and video sequences as carriers to improve traditional algorithm research and to perform motion gesture recognition. Through performance analysis, this paper explores the traditional algorithm and uses parameter analysis to improve the feature extraction and classification of traditional algorithms. Moreover, this paper uses the multi-scale feature approximation calculation method to improve the speed of the algorithm to extract features, and the algorithm is tested …using the UCF motion data set and the self-created motion data set. In addition, this paper obtains representative motion video through data collection to test the effectiveness of the proposed algorithm. The research shows that the proposed algorithm has good performance and can provide theoretical reference for subsequent related research. Show more

Keywords: Machine learning, sports, static image, gesture recognition

DOI: 10.3233/JIFS-179203

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6205-6215, 2019

Authors: Wei, Cheng | Dan, Li

Article Type: Research Article

Abstract: Estimating the compensation risk of agricultural insurance is a hotspot of current research. The related research mainly focuses on the calculation and simulation of catastrophe risk that agricultural insurance may face. On the whole, the compensation risk of agricultural insurance mainly comes from the agricultural disasters, especially the agro meteorological disasters. Compared with property insurance, the overall compensation rate of agricultural insurance is much higher than that of property insurance, so agricultural insurance belongs to high-risk business operation. In the research, the support vector machine is used as the research technology, and the forecast model corresponding to the insurance market …is constructed. At the same time, this paper constructs SVM prediction model and VAR-based SVM prediction model. Finally, the prediction accuracy of the SVM prediction model and the VAR-based SVM prediction model are compared and analyzed. The research shows that the prediction accuracy of VAR-based SVM prediction model is higher, that is, it is easier to draw near-realistic prediction results based on parameter optimization. This paper summarizes the research, puts forward its inadequacies and merits, and provides theoretical reference for subsequent related research. Show more

Keywords: Parameter optimization, machine learning, agricultural insurance, forecast model

DOI: 10.3233/JIFS-179204

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6217-6228, 2019

Authors: Xu, Wanxiao | Ding, Mingjie

Article Type: Research Article

Abstract: The accelerated development of urbanization in China started with economic globalization and industrialization, and also in the process of economic system transition. Generally speaking, urbanization is an important indicator of a region’s economic development and social development. Urbanization equity is an important direction of sustainable economic and social development. From the economic dimension, urbanization can promote division of labor, specialization and accumulation of human capital through agglomeration effect. This paper analyzes the social equity and urbanization by using fuzzy logic and factor analysis model. Under the condition of market economy, migrant workers have no competitive advantage in the labor market …because of their low educational level. At the same time, the treatment of migrant workers in social security, cultural education and economic welfare is lower than that of urban residents. Under the unbalanced economic development reality, the economic absorption effect leads to the migrant workers rushing to the developed big cities. The results shows that by taking the dimensions of social justice of the rural migrant worker as the independent variable, psychological urbanization for the dependent variable, the regression Equation of F value is 90.424, P  = 0.000, less than 0.05 level of significance. Also, we make correlation analysis on all factors of social justice and urbanization. The experimental results show the effectiveness of proposed method. Green building is the development of sustainable development concept in architectural field. While the construction industry has brought great benefits to the development of national economy, its high investment, high pollution and inefficient development mode has also produced a huge energy load. Therefore, from the perspective of environmental and economic sustainability, the development of green buildings is particularly important. In this paper, the author makes economic benefit analysis of green building based on fuzzy logic and bilateral game model. By introducing such factors as economic benefits, cognition and government policies, this paper construct an evolutionary game model, which provides a basis for improving the economic benefits of green buildings. The results show that the first factor affecting enterprise decision-making is the incremental profit of green building developers, followed by the government’s incentive policy. After the evolution of the market, the final strategic choice will be stabilized to higher economic benefits. Generally speaking, green buildings need to effectively control incremental costs and consider scale benefits. Through management efficiency innovation and policy stimulation, the problems of huge investment cost and long payback period can be solved, so as to improve the economic benefits of green building development. Show more

Keywords: Urbanization rate, social security, fuzzy model, factor analysis

DOI: 10.3233/JIFS-179205

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6229-6240, 2019

Authors: Liwei, Sun

Article Type: Research Article

Abstract: At present, the application of artificial intelligence in the identification and classification of sports technology is still relatively small, and it is difficult to effectively improve the training and competition quality of athletes. Based on this, this study takes badminton as an example for analysis. Moreover, based on the complexity and multi-deformation of this motion, this study uses machine learning as the basic algorithm to design a real-time classification algorithm for badminton action. At the same time, this paper improves the traditional algorithm, designs an improved training model, and verifies the effectiveness of the design algorithm by experimental method. In …addition, this paper constructs a feature statistics and pace training system with the support of machine learning algorithms through statistical analysis and statistical badminton technical features and realizes the intelligentization of badminton batting action classification and recognition. Finally, this paper designs a comparative test for system functional testing. The system test shows that the system can effectively improve the action classification and recognition effect and can provide theoretical reference for subsequent related research. Show more

Keywords: Machine learning, badminton, motion recognition, action classification

DOI: 10.3233/JIFS-179206

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6241-6252, 2019

Authors: Yuan, Xiaoyi

Article Type: Research Article

Abstract: The lack of effective evaluation of online education is a worldwide malpractice, and it is impossible to help students improve the correctness of online learning choices through existing reviews. Based on the current mainstream sentiment lexicon and text sentiment analysis, the authors use machine learning method to analyze the sentiment orientation of the legal course review text, through method that combines PMI and SVM. At the same time, this paper uses LibSVM tool to train and predict data, collect and pre-process data through network data collection, and, based on traditional algorithms, propose improved experimental scheme based on their respective advantages …and disadvantages. In addition, the model proposed in this study is used to classify and process the emotional text, and the two methods are combined to obtain the final result. Finally, this paper combines experiments to analyze the performance of the comprehensive model proposed in this study. The research shows that the classification effect of the text sentiment analysis of model is good, it can be applied to practice, and it can provide theoretical reference for subsequent related research. Show more

Keywords: Support vector machine, algorithmic optimization, online course, data network

DOI: 10.3233/JIFS-179207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6253-6263, 2019

Authors: Xiaolong, Zhang

Article Type: Research Article

Abstract: Athletes have a large amount of video information, so how to capture effective information is the key to improving athletes’ training efficiency and improving the quality of the game. From the perspective of deep learning, this study analyzes and improves traditional algorithm models based actual needs, and jointly learns multi-scale features. At the same time, in view of the problem of over-fitting in the model training process, this study uses the sparse pyramid pool strategy to adjust the pool parameterization process and reduce the complexity of feature description. In addition, the research designs experiment to analyze the performance of the …improved algorithm model and select the appropriate database to analyze the recognition effect of the algorithm model. The research shows that the algorithm of this research has a certain improvement in the recognition effect of athletes, and the recognition effect matching the artificial design features can be obtained, and it can provide theoretical reference for subsequent related research. Show more

Keywords: Deep learning, convolution algorithm, motion recognition, database management, deep learning

DOI: 10.3233/JIFS-179208

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6265-6274, 2019

Authors: Chaoming, Liang

Article Type: Research Article

Abstract: Ball sports have great variability in the game and the intelligent control of the rules of ball movement can effectively improve the training effect of athletes. However, the current research on artificial intelligence of spherical motion trajectory prediction points is basically blank. Based on this, this study is based on deep learning technology, and obtains the main experimental data through network data collection in the research and builds the table tennis spatial position image data set under various environments with accurate annotation based on the traditional deep learning. At the same time, the convolutional neural network is used as the …location recognition algorithm, and a prediction algorithm for predicting the trajectory of table tennis is proposed based on the recurrent neural network. In addition, this paper designs comparative experiments to analyze the effectiveness of the algorithm model, and evaluates the real-time recognition, location and trajectory prediction capabilities, and conducts quantitative analysis. The research shows that the algorithm has certain practical effects and can provide theoretical reference for subsequent related research. Show more

Keywords: Deep learning, neural network, trajectory, recognition algorithm, prediction model

DOI: 10.3233/JIFS-179209

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6275-6285, 2019

Authors: Yue, Wu

Article Type: Research Article

Abstract: With the rapid expansion of chain network, enterprises meet the consumption demand scattered around in a large range. In this paper, SOM neural network algorithm is introduced for empirical test. Design includes the structure of the fuzzy neural network identification and parameter identification, structural identification include input space division and the number of fuzzy rules to determine. Through summarizing and analyzing the characteristics of chain retail enterprises, this paper proposes to build a hierarchical and differentiated incentive mechanism by cultivating retail culture. The result shows that the knowledge staff is been higher the education level, the work creativity is stronger, …cooperates the demand to the team members. In the era of the knowledge economy, knowledge has replaced capital as the core source of the enterprise core competence. The performance evaluation of knowledge workers is complex and the performance of the general staff is often easier to get a more objective evaluation. In conclusion, performance characteristics of knowledge workers should include general knowledge staff quality, knowledge staff performance behavior and performance results three aspects of characteristics. Show more

Keywords: SOM neural network, fuzzy model, chain enterprises, performance analysis

DOI: 10.3233/JIFS-179210

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6287-6300, 2019

Authors: Li, Bin | Wei, Xing | Li, Chao | Ding, Shuai

Article Type: Research Article

Abstract: Due to the lack of uniform standards for pathological cell detection, it is difficult to identify. In order to improve the accuracy of pathological cell identification, this study combines the actual situation of cell detection based on traditional particle algorithm to construct a C-V model based on level set algorithm and curve evolution theory, which realizes the effective separation of different substances inside the cell. At the same time, in order to effectively extract the characteristics of cell images, this paper uses the global research method to extract the features of the research object and adopts the improved gray level …co-occurrence matrix to extract the texture features, thus effectively improving the feature extraction quality. In addition, in order to study the accuracy of the algorithm model identification in this study, this paper designs a comparative experiment for performance analysis. The research shows that the proposed algorithm model has good performance, can achieve accurate recognition and feature extraction of pathological cells, has certain practical effects, and can provide theoretical reference for subsequent related research. Show more

Keywords: Particle algorithm, neural network, cell detection, model

DOI: 10.3233/JIFS-179211

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6301-6313, 2019

Authors: Gao, Shuyan | Xu, Jiaqi | Lu, Weiheng

Article Type: Research Article

Abstract: Traditional nuclear magnetic resonance technology has grayscale inhomogeneity in brain tumor detection, which directly affects the formulation of follow-up treatment plans. In order to improve the detection effect of nuclear magnetic resonance on brain tumors, this study uses a convolutional neural network as the basis algorithm to construct an algorithm model suitable for multimodal MRI image recognition. At the same time, combined with the actual case, this paper uses the model to segment and identify brain tumors, and this paper combines the principle of machine learning and collects data for data training to construct a multi-channel deep deconvolution network model. …In addition, in order to explore the effectiveness of the algorithm in this study, the performance analysis was carried out by comparative experiment method, and the multi-faceted performance of the model was studied, and the corresponding test result images were obtained. Through experimental comparison, it can be seen that the algorithm model constructed in this study has certain validity, can be applied to practice, and can provide theoretical reference for subsequent related research. Show more

Keywords: Nuclear magnetic resonance, brain tumor, diagnosis, segmentation, convolutional neural network

DOI: 10.3233/JIFS-179212

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6315-6324, 2019

Authors: Lijun, Cheng | Yubo, Zhang

Article Type: Research Article

Abstract: The Internet of Things (IOT) is the main technical support of smart agriculture. The sensor equipment of the Internet of Things (IOT) in agriculture is developing in the direction of low cost, self-adaptation, high reliability and low power consumption. In the future, the sensor network will gradually have the characteristics of distributed, multi-protocol compatibility, self-organization and high throughput. In this paper, the authors analyze the intelligent agricultural system and control mode based on fuzzy control and sensor network. Intelligent agriculture is based on the most efficient use of various agricultural resources to minimize agricultural energy consumption and costs. It is …supported by Internet of Things technologies such as comprehensive perception, reliable transmission and intelligent processing. Using ROF technology, the WiFi signal is pulled far, and the wireless coverage is expanded greatly. At the same time, through the combination of wireless sensor technology such as ZigBee, the transmission and centralized control of sensing signals are realized, and the monitoring system of intelligent agricultural greenhouse is established. The simulation results show that the system can effectively improve the level of intelligence and information of agricultural greenhouse management, and greatly improve crop production efficiency. Show more

Keywords: Intelligent agriculture, wireless technology, sensor networks, fuzzy control

DOI: 10.3233/JIFS-179213

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6325-6336, 2019

Authors: Li, Wenxian

Article Type: Research Article

Abstract: Reasonable fire risk assessment system can demonstrate the occurrence of fire and ensure the safe evacuation of fire. The selected indicators of the evaluation system play a fundamental role in the establishment of the system. In the evaluation model, the general problem is transformed into a specific mathematical model by using the method of fuzzy information processing, which makes the evaluation result more direct and measurable. This paper uses a measure of feature attributes to measure the contribution of clusters, that is, the method of calculating the weight of features. When the value of the equilibrium discriminant function reaches the …minimum value, the clustering result under the optimal condition can be obtained. Then, the author analyzes the fire risk assessment and factor analysis of buildings based on multi-target decision and fuzzy mathematical model. The simulation results show that the improved fuzzy model proposed in this paper makes the calculation results more accurate. The fire risk analysis and control system based on the theory of fuzzy information processing can be widely used in various high-rise buildings to ensure safety. Show more

Keywords: Multi-objective decision, high-rise building, fire risk, fuzzy mathematics

DOI: 10.3233/JIFS-179214

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6337-6348, 2019

Authors: Wenwen, Liang

Article Type: Research Article

Abstract:  In order to realize the intelligent evaluation of effective teaching quality and make up for the lack of research in this aspect, in the research, BP neural network is used as the basis for model construction analysis. Political education in colleges and universities is an important course, and its teaching quality evaluation is particularly important. Through comparative analysis, LMBP is selected as the learning algorithm, and the neural network evaluation model mechanism of college classroom teaching quality evaluation system is determined through theory and practical methods, and the simulation model is simulated by MATLAB as a simulation tool. At the …same time, this paper uses the experimental method to carry out simulation training experiments in the MATLAB neural network toolbox, select the training algorithm for comparative analysis, and display the results in the form of statistical graphs. In addition, this paper sets the convergence speed and error curve as evaluation indicators, determines the appropriate training algorithm, and verifies the validity of the model. The research indicates that the BP teaching quality evaluation model based on BP neural network is a reasonable and feasible evaluation model and can provide theoretical reference for subsequent related research. Show more

Keywords: BP neural network, teaching quality, model, training function, simulation analysis

DOI: 10.3233/JIFS-179215

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6349-6361, 2019

Authors: Peng, Qin

Article Type: Research Article

Abstract:  With the full spread of various IT application systems, a large number of business data are stored in the business systems of enterprises. In this paper, the author analyzes the aviation industry management mode based on big data analysis. In this paper, the author analyses aviation industry management model and exchange rate index analysis based on error correction model and fuzzy mathematics. The BP algorithm uses the error of the output layer to estimate the error of the direct predecessor layer of the output layer, and then gradually estimates the error forward, and thus, the error of all layers is …obtained. The weights and thresholds of the layers are adjusted according to the error so that the modified network output can approach the expected value. The aviation industry data include both the financial and internal data of airlines, and the external data such as flight information and user data. From the ETL process, building an enterprise data warehouse is an important strategy for the development of the aviation industry. It has a positive effect on the application of automatic data mining and business intelligence in the aviation industry. On this basis, we put forward relevant suggestions for aviation industry management. Show more

Keywords: Big data, aviation industry, operation management, error correction model, fuzzy mathematics

DOI: 10.3233/JIFS-179216

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6363-6375, 2019

Authors: Zhen, Zhen | Yanqing, Yao

Article Type: Research Article

Abstract: Technological innovation in manufacturing industry is a kind of R&D activity that produces new technologies, including input and output of technological innovation. In this paper, the authors analyze the lean production and technological innovation in manufacturing industry based on SVM algorithms and data mining technology. Data mining can discover novel, effective, potential and ultimately understandable data patterns from a deeper level, and encode the data to predict the development trend of enterprises. The machine learning support vector machine method is used to analyze and model the collected data. At the same time, we constructed a decision tree using random forest, …and explained the significance of the training algorithm through the visualization results. The simulation results show that learning growth dimension and market dimension have the greatest impact on business model innovation. In the context of TEC, business model innovation must pay attention to market grasp and customer demand oriented, so as to improve the competitiveness of manufacturing enterprises. Show more

Keywords: SVM Algorithms, data mining, manufacturing enterprises, science and technology level

DOI: 10.3233/JIFS-179217

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6377-6388, 2019

Authors: Yangjun, Ren | Chuanxu, Wang | Lang, Xu | Chao, Yu | Suyong, Zhang

Article Type: Research Article

Abstract: Using the panel data for China’s 30 provinces from 2008 to 2016, this paper analyzes the impact of producer services agglomeration on green economic efficiency at its spillover effects, through spatial autocorrelation test and the establishment of spatial econometric models. It comes to the results as follows: First, China’s regional green economic efficiency is significant positive spatial dependence. Second, the producer services specialized agglomeration not only inhibits the green economic efficiency of one region but also has significantly negative spatial spillover effects on adjacent areas, while the producer services diversified agglomeration only enhance the green economic efficiency in the region. …Third, the impact of the agglomeration mode selection of producer services industry on green economic efficiency in the eastern region is basically consistent with the empirical analysis at the national level, while the green economic efficiency improvement in the central region only benefits from producer services specialized agglomeration, and the green economic efficiency in the western region is not significantly affected by the producer services agglomeration mode selection. Show more

Keywords: Production services agglomeration, green economic efficiency, spatial Durbin model, spillover effects

DOI: 10.3233/JIFS-179218

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6389-6402, 2019

Authors: Qiang, Qunli

Article Type: Research Article

Abstract: Currently, there is a certain fluctuation in the real estate industry, so it is particularly important to analyze the solvency of real estate enterprises. In order to find a reliable model suitable for studying the difference in house prices, this study collects the research data through data collection, and uses the K-means clustering method to construct the corresponding model as a basic research in combination with the machine learning research method. At the same time, this paper compares the analysis effects of several common machine learning models and finds the advantages and disadvantages of these methods through mathematical statistics. In …addition, combined with practice, this paper constructs a nonlinear generalized additive model, and based on machine learning technology, validates the validity of the model based on data analysis, the collected predictors. In view of the improvement of the solvency of real estate enterprises, diversified operation of real estate enterprises can maintain reasonable cash flow and make up for the defect of poor liquidity of real estate. Furthermore, this paper uses the stability method to find the optimal model. In addition, the generalized additive model effectively reveals the complex nonlinear relationship between continuous predictors and house prices. Through research, it can be seen that the nonlinear generalized additive model based on machine learning can play an important role in real estate industry forecasting and has certain theoretical reference significance for subsequent related research. Show more

Keywords: Real estate, generalized additive model, machine learning, K-means Algorithm

DOI: 10.3233/JIFS-179219

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6403-6414, 2019