Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Xiong, Shuiping

Article Type: Research Article

Abstract: In order to improve the modulation recognition algorithm effect of an optical communication system, an improved modulation recognition algorithm technology based on wavelet transform on the time-varying optical communication system is designed. Firstly, considering the time-varying effect of noise on the communication system, wavelet transform is introduced to pre-process the signal of the optical communication system, extracting the characteristic number of modulation recognition of optical communication system, and a classifier of modulation recognition is established by data mining technology to realize modulation recognition technology of optical communication system. Finally, several typical modulation modes of the optical communication system are tested …by simulated experiments. In this paper, several typical modulation modes are identified accurately, and real-time on-line analysis of modulation recognition is realized. In the optical communication system, the recognition accuracy of the modulation pattern is higher than other modulation recognition technologies, which has high practical application value. Show more

Keywords: Optical communication, time-varying characteristics, modulation recognition, pattern recognition

DOI: 10.3233/JIFS-189424

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5845-5852, 2021

Authors: Li, Chunya | Li, Yan

Article Type: Research Article

Abstract: This paper establishes a theoretical model of third-party mobile payment user satisfaction based on the ASCI model and proposes research hypotheses. Then, the questionnaire survey method is used to collect sample data and carry out reliability and validity test. After the test is passed, structural equation modeling (SEM) is used to verify the research model and hypothesis. Finally, the analysis concludes: perceived quality and perceived value will have a positive impact on user satisfaction; user expectations will affect user satisfaction through perceived quality and perceived value; the impact of perceived risk on user satisfaction is not obvious. Propose reasonable suggestions …for third-party mobile payment companies based on the research conclusions. Show more

Keywords: Third-party mobile payment, internet of things, structural equation model (SEM)

DOI: 10.3233/JIFS-189425

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5853-5861, 2021

Authors: Yi, Jing | Liu, Peiyu | Wang, Zhihao | Liu, Wenfeng

Article Type: Research Article

Abstract: In the study filed of rumor spreading, kill rumor or dispel rumor is very important in order to control rumor spreading and reduce the bad influence of the rumor. In the previous studies, rumor clarification is mostly finished by relying on external media or news reports instead of intervening and controlling from inside the network, which causes that the speed of rumor clarification is far lower than the speed of rumor spreading, and it is not ideal for the effect of rumor clarification. In this paper, a new Twin-SIR spreading model is proposed, in which, a rumor clarification node named …as “rumor dispeller” with the spreading ability is introduced. The rumor dispeller is involved in the spreading process of the model together with the rumor spreader to control the spreading of rumor and thus to achieve the purpose of clarifying rumor. At the same time, during the process of building the model, we also apply the traditional media as a spreading parameter to the spreading process of the model. We built the mean-field equation of the model and then implemented further analysis of the model on homogeneous networks and heterogeneous networks. Through experimental simulations, the “rumor dispeller” was found to have the ability to reduce the spread of rumor spreading, and that the selection of the initial “rumor dispeller” node can affect the effect of rumor spreading, and at the same time, the external media have an important influence on rumor clarification. These conclusions have a new function for guiding us to study the mechanism of rumor spreading. Show more

Keywords: Online social network, spreading model, rumor dispelling, twin-SIR model

DOI: 10.3233/JIFS-189426

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5863-5874, 2021

Authors: Lu, Zhengjie

Article Type: Research Article

Abstract: In this paper, a two-degree-of-freedom manipulator is taken as the research object, and the relevant dynamic model is established, the iterative learning controller is designed, and the trajectory tracking control of the manipulator is carried out by using the iterative learning control algorithm. Iterative learning control (ILC) has a better control effect on a two-degree-of-freedom manipulator with repetitive motion characteristics for its non-linear system. In the case of disturbance, a PD-type iterative learning control law is designed. With the increasing number of iterations of the system, the required correction interval is shortened by modifying the gain matrix in real time …in the interval, so as to accelerate the convergence speed. The simulation results show that the convergence speed of PD-type ILC is faster than that of P-type ILC, and the convergence effect of PD-type ILC with disturbance is better than that of traditional disturbance-type ILC. The industrial robot system is guaranteed to have good dynamic performance. Show more

Keywords: Two-degree-of-freedom manipulator, PD learning law, iterative learning algorithm

DOI: 10.3233/JIFS-189427

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5875-5882, 2021

Authors: Tseng, Tsui-Yuan | Luo, Qinglan

Article Type: Research Article

Abstract: With the development of science and technology and the continuous improvement of people’s living standards, the traditional staff quality evaluation can no longer meet the needs of production and life, and the BP neural network has also appeared many shortcomings in practical applications. This article mainly studies the company’s employee quality evaluation model based on BP neural network. This article first collects and preprocesses employees’ usual performance data, and then predicts their corresponding quality scores based on BP neural network. And use MATLAB software to simulate the constructed prediction model, and finally develop a complete set of employee performance data …prediction system based on this model, so as to achieve the purpose of employee quality evaluation. The experimental data in this paper shows that the average relative error of model training output tends to be stable. After the 40th iteration of training, the average relative error of model training can reach 0.0128. After the prediction model training was completed, 15 sets of verification samples were used to verify the model. The verification results found that the average relative error of the model converged, so the model did not overfit. Experimental results show that although BP neural network has two excellent functions of adaptive and nonlinear approximation, it can solve the complex nonlinear relationship between normal performance and overall performance. But BP neural network still has its own inevitable shortcomings in some aspects. For example the redundancy between the employee scoring sample data; the problem that the input variable dimensionality is too high, which leads to the low efficiency of the model; the fuzzy neural network is easy to fall into the local optimum and it is difficult to find the global optimum. Show more

Keywords: BP neural network, employee quality evaluation model, fuzzy system, fit state, model simulation

DOI: 10.3233/JIFS-189428

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5883-5892, 2021

Authors: Qian, Yu

Article Type: Research Article

Abstract: With the development of wireless sensor technology, more and more fields are applied to wireless sensor technology, and the design and implementation of the flight scene system are in it. The purpose of this study is to design and implement a flight visual simulation system using sensor technology and QAR data. The method of this study is to first establish the mathematical model of the aircraft and then calculate the aerodynamic force and torque of each part of the aircraft respectively to obtain the nonlinear dynamic model of the aircraft, and finally realize the whole simulation model on the MATLAB …platform. The results show that the main motion variables corresponding to the conjugate complex root (0.0530.287i) are the velocity and pitch angle of the aircraft, and they all change slowly and long period. The period is 21.9 seconds, and the frequency doubling time (LN2 / 0.053 + 0.287i) is 11.0 seconds, which meets the requirements of flight quality specification. It is concluded that the flight visual simulation system in this study can well describe the flight trajectory and observe the external scene. The simulation system uses computer graphics and image technology to realize real-time and accurate simulation and reproduction of the flight status and trajectory of the aircraft, which can provide an intuitive and convenient simulation analysis method for the exploration of new aerospace technology and engineering design. Show more

Keywords: Sensor technology, QAR data, flight visual system, simulation design

DOI: 10.3233/JIFS-189429

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5893-5903, 2021

Authors: Lang, Kun | Zhao, Yuxin

Article Type: Research Article

Abstract: In recent years, with the change of people’s living habits, food delivery has become more and more popular. Along with this is the rapid growth of takeaway distribution. It is significant to improve the accurate prediction of the take-out order quantity since it can reduce unnecessary losses for the merchants. The Cloud computing system is the main platform for processing massive data. Applying cloud computing resource scheduling to the forecasting of takeaway orders will greatly help merchants. The research purpose of this paper is to study the cloud computing resource scheduling based on improved ANN model takeaway order volume prediction. …This paper improves the ANN model and proposes a cloud computing resource scheduling method based on improved ANN model takeaway order volume prediction. An experimental test was performed to verify the reliability of the proposed method. The results of this study show that the proposed method can accurately predict takeaway orders and contributes to reasonable resource scheduling. Show more

Keywords: Improved ANN model, cloud computing, resource scheduling, takeaway order volume prediction

DOI: 10.3233/JIFS-189430

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5905-5915, 2021

Authors: Duan, Rongkai | Sun, Pu

Article Type: Research Article

Abstract: With the continuous innovation of science and technology, the mathematical modeling and analysis of bodily injury in the process of exercise have always been a hot and difficult point in the research field of scholars. Although there are many research results on the nonlinear classification of the basketball sports neural network model, usually only one model is used, which has certain defects. The combination forecasting model based on the ARIMA model and neural network based on LSTM can make up for this defect. In the process of the experiment, the most important is the construction of the combination model and …the acquisition of volunteer data in the process of the ball game. In this experiment, the ARIMA model is used as the linear part of the data, and LSTM neural network model is used to get the sequence of body injury. The results of the empirical study show that: it is reasonable to divide the injury of thigh and calf in the process of basketball sports, which is very consistent with the force point of the human body in the process of sports. The results of the two models predicting the average degree of bodily injury for many times are about 0.32 and 0.38 respectively, which are far less than 1. The execution time of the program for simultaneous prediction on the computer is about 1 minute, which is extremely effective. Show more

Keywords: Nonlinear classification, neural network, radial basis function, time-series model, basketball

DOI: 10.3233/JIFS-189431

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5917-5926, 2021

Authors: Lan, Zimian

Article Type: Research Article

Abstract: In this paper, we propose a new iterative learning control algorithm for sensor faults in nonlinear systems. The algorithm does not depend on the initial value of the system and is combined with the open-loop D-type iterative learning law. We design a period that shortens as the number of iterations increases. During this period, the controller corrects the state deviation, so that the system tracking error converges to the boundary unrelated to the initial state error, which is determined only by the system’s uncertainty and interference. Furthermore, based on the λ norm theory, the appropriate control gain is selected …to suppress the tracking error caused by the sensor fault, and the uniform convergence of the control algorithm and the boundedness of the error are proved. The simulation results of the speed control of the injection molding machine system verify the effectiveness of the algorithm. Show more

Keywords: Nonlinear system, iterative learning control, sensor fault, initial state error, λ norm

DOI: 10.3233/JIFS-189432

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5927-5934, 2021

Authors: Lin, Feiting

Article Type: Research Article

Abstract: The potato itself has high nutritional value, strong adaptability, long industrial chain and extremely stable yield. At the same time, due to the rich variety of processed products, the further improvement of China’s social and economic level is greatly strengthened. In February 2016, the Ministry of Agriculture issued guiding opinions on promoting the development of the potato industry, which took potato as the main food product for industrial development. The central government attaches great importance to the rapid development of the potato industry, but at the same time, it also exposes many problems, which affect the production and development of …the potato industry to a large extent. In order to change this problem, the relevant staff needs to strengthen the application of intelligent technology, so as to improve the level of potato production and processing and improve the competitive advantage of China’s potato industry. There are many types of research on the potato industry in China, but most of them focus on Cultivation and maintenance skills, and there is almost no research on market competition of agricultural products economic management based on the intelligent system. Based on the current situation of potato production in China, combined with the advantages of an intelligent system, this paper analyzes its competitive advantages and disadvantages from the perspective of economic management, and constructs the industrial competitiveness analysis model with the intelligent system as the core technology, and analyzes and discusses the adverse factors affecting the competitiveness. And from the perspective of international trade, the export competitiveness of China’s potato industry was analyzed. Finally, we collected Ximeng as the sample of this study and verified the core points of improving competitiveness from the research. In this paper, based on the intelligent system management of the potato planting industry on agricultural product economic management of market competition optimization research, to a certain extent, filled the domestic blank, has high research and promotion value. Show more

Keywords: Potato planting industry, intelligent system, agricultural product economic management, market competitiveness

DOI: 10.3233/JIFS-189433

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5935-5944, 2021

Authors: Cui, Di

Article Type: Research Article

Abstract: Image segmentation is very important for various fields. With the development of computer technology, computer technology has become more and more effective for image segmentation, and it is studied on the basis of partial differential equations. The curve representation method in plane differential geometry is expounded, with the SegNet-v2 segmentation model analyzed and tested in medical image segmentation. The test results show that the partial differential equation image segmentation algorithm can achieve more accurate segmentation, especially in medical image segmentation, which can achieve good results, and it is worth in practice to further promote.

Keywords: Partial differential equation, image segmentation, algorithm analysis

DOI: 10.3233/JIFS-189434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5945-5952, 2021

Authors: Wu, Manxia | Wang, Wen

Article Type: Research Article

Abstract: A large number of high slopes will be formed in the construction of expressways in many mountainous areas, which is very unfavorable to the construction of local expressways. Effective monitoring methods are essential to solving these problems, and the Internet of Things technology is a good dynamic monitoring method. Therefore, it is necessary to carry out research on the dynamic monitoring system of rock and soil high slope based on the Internet of Things perception. The purpose of this article is to solve the problem of dynamic monitoring of high slopes, taking highway slopes in Chongqing as an example, making …full use of the literature method, field investigation method, regression analysis method, time series analysis method, and theoretical analysis method. Through real-time monitoring of the entire process of rock and soil high slope construction in different locations in a certain area in the southwest, and continuously adjusting and verifying the monitoring situation and solving related problems, the high slope instability at this point was accurately monitored And at any time find the weak links in the construction process of high slopes, and further find its potential quality and safety risks, and then establish a comprehensive monitoring system and early warning system. The research results show that this comprehensive monitoring and early warning system improves the accuracy of early warning and monitoring from qualitative judgment to quantitative analysis and from macro to micro monitoring, and can provide a reference for other types of projects. Show more

Keywords: Internet of things, high slope, dynamic monitoring, geotechnical environment

DOI: 10.3233/JIFS-189435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5953-5962, 2021

Authors: Tang, Guanghai | Zeng, Hui

Article Type: Research Article

Abstract: Cloud computing, as a product of the fusion and development of computer technology and Internet technology, not only realized the innovation of IT technology but also A major revolution in the IT business model will bring unprecedented and profound changes to the information industry. The main purpose of this article is to study the collaborative management and control method of blockchain in a cloud computing environment. This article mainly uses the blockchain consensus algorithm to analyze and research the blocking technology in the logistics supply chain, and solves the supplier’s benefit formula step by step; also uses the CloudBTF algorithm, …Max-min algorithm, FCFS of cloud computing Algorithm, and compare the efficiency and security of the three methods to get the most conducive to the collaborative management and control of the blockchain. The experimental results of this paper show that blockchain collaborative management in a cloud computing environment can greatly improve the security of massive data storage and the collaborative distribution of data. Among them, the use of cloud computing platform priority algorithms can improve system load balancing by up to 12%, while Using the cloud computing platform FCFS algorithm can improve system load balancing by up to 15%. Show more

Keywords: Cloud computing, blockchain control, collaborative management, control method, cloud BFT algorithm

DOI: 10.3233/JIFS-189436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5963-5973, 2021

Authors: Liu, Shuqiang | Zhao, Dawei

Article Type: Research Article

Abstract: In general, there are a lot of uncertainties in uncertain information, natural language, and human knowledge. The conclusion can be better deduced by using an approximate reasoning method, while a fuzzy intelligent system can deal with uncertain data and rule evaluation information systems. In order to better explore diffusion and economic growth, this paper constructs a fuzzy intelligent system based on the DSGE model and uses this system to analyze diffusion and economic growth. In order to verify the feasibility of this system, we test the response time and accuracy of the system. In addition, we also use the system …to simulate diffusion and economic growth. The results show that with the increase of the task amount, the gap between the actual response time and the expected response time of the fuzzy intelligent system based on the DSGE model increases. When the task quantity is 20, the expected response time is 2.31 and the actual response time is 2.24. When the task quantity is 40, the expected response time is 2.5 and the actual response time is 2.36. The larger the task quantity is, the faster the response time of a fuzzy intelligent system based on the DSEG model is. Therefore, the fuzzy intelligent system based on the DSEG model has good performance and can analyze diffusion and economic growth well. Show more

Keywords: DSGE model, fuzzy intelligence system, system performance, diffusion, and economic growth

DOI: 10.3233/JIFS-189437

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5975-5983, 2021

Authors: Wang, Linlin

Article Type: Research Article

Abstract: With the continuous development of computer science and technology, symbol recognition systems may be converted from two-dimensional space to three-dimensional space. Therefore, this article mainly introduces the symbol recognition system based on 3D stereo vision. The three-dimensional image is taken by the visual coordinate measuring machine in two places on the left and right. Perform binocular stereo matching on the edge of the feature points of the two images. A corner detection algorithm combining SUSAN and Harris is used to detect the left and right camera calibration templates. The two-dimensional coordinate points of the object are determined by the image …stereo matching module, and the three-dimensional discrete coordinate points of the object space can be obtained according to the transformation relationship between the image coordinates and the actual object coordinates. Then draw the three-dimensional model of the object through the three-dimensional drawing software. Experimental data shows that the logic resources and memory resources occupied by image preprocessing account for 30.4% and 27.4% of the entire system, respectively. The results show that the system can calibrate the internal and external parameters of the camera. In this way, the camera calibration result will be more accurate and the range will be wider. At the same time, it can effectively make up for the shortcomings of traditional modeling techniques to ensure the measurement accuracy of the detection system. Show more

Keywords: Symbol recognition system, 3d reconstruction, binocular stereo vision, feature extraction, stereo matching

DOI: 10.3233/JIFS-189438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5985-5994, 2021

Authors: Bian, Fei | Wang, Xuansheng

Article Type: Research Article

Abstract: School enterprise cooperation is of great strategic significance to China’s manufacturing industry. The Party Central Committee has repeatedly proposed to strengthen the integration of industry and education and deepen the cooperation between schools and enterprises. In recent years, experts and scholars at home and abroad have been from different perspectives, although they have achieved fruitful results, there are also problems such as insufficient attention to theoretical research, relatively backward research, narrow research scope, and so on. In view of this phenomenon, this paper will study a new school-enterprise cooperation mechanism based on the improved decision tree algorithm. The research of …this paper is divided into three parts. First, after analyzing the advantages and disadvantages of the algorithm, the algorithm of the decision tree is improved, which makes the improved algorithm more suitable for the field of school-enterprise cooperation. Then, based on cloud computing and intelligence, this paper establishes a new model of school-enterprise cooperation platform, which solves some problems of data management and information exchange in school-enterprise cooperation. Finally, in order to make the cooperation mechanism of this paper better used in practice, this paper builds an online and offline hybrid training base, hoping to make the cooperation between schools and enterprises closer through the training base. In order to test the effect of the cooperation model, this paper takes school as the experimental model. After investigation and research, it is believed that thanks to the school-enterprise cooperation mechanism in this paper, the cooperative enterprise of school has been greatly improved in the past three years, and the willingness of enterprises to cooperate has become more and more strong. No matter students, teachers, or enterprises are reaping huge benefits under this cooperation mechanism, it is a suit for extensive promotion The school-enterprise cooperation mechanism of Guangyun. Show more

Keywords: Improved decision tree algorithm, school-enterprise cooperation, cloud computing, combination of production and learning

DOI: 10.3233/JIFS-189439

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 5995-6005, 2021

Authors: Chen, Zhuo | Chen, Ruoxi | Chen, Songtao

Article Type: Research Article

Abstract: With the development of urbanization, the application of GIS technology is more and more extensive. This study mainly discusses the development of urban planning intelligent management information system based on GIS. To design and build a rule-detailed spatial data model, provide the physical model and the data model corresponding to the logical layer from top to bottom in all steps, based on the attribute information stored in the Geodatabase model. According to the parameters set, connect to the database through the Oracle Connection class. The defined query criteria are converted into SQL statements that are executed using the Oracle Command …class. Multi-source data integration middleware integrates various data formats with a GIS software format conversion tool or direct reading tool and then uses the geometric encoding semantics of data dictionary to represent the integrated data of system data model after merging. Property queries use the interactive search function for properties and spatial information to query the land use index for a particular area of the chart. If there is a scene roaming request from the input device, the 3D scene needs to be adjusted according to the input. Display the scene effects of a 3D virtual demonstration on a computer monitor. Start the GIS management operation function to deal with the case, and realize the user’s management of the urban planning system function with the concept of stratification. Fuzzy recognition mode is applied to identify the degree of the environmental impact of eco-city planning. The impact of urban planning on the environment is H ≈ 0.11 (0.1 < H < 1), which meets the expected standard. The results show that the system demand evaluation designed in this study is good, and the overall operation of the system is relatively stable, which plays a promoting role in urban planning. Show more

Keywords: GIS technology, urban planning, intelligent management, system research

DOI: 10.3233/JIFS-189440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6007-6016, 2021

Authors: Ding, Qiaoying

Article Type: Research Article

Abstract: The financial market is changing rapidly. Since joining the WTO, our country’s financial companies have faced pressure from dual competition at domestic and abroad. The complex internal and external environment has forced financial enterprise managers to improve risk prevention awareness, early warning and monitoring, so as to responding to emergencies and challenges in the financial market. However, traditional forecasting and analysis methods have problems such as large workload, low efficiency, and low accuracy. Therefore, this article applies intelligent computing to the forecast of financial markets, using related concepts of fuzzy theory and Internet intelligent technology, and proposes to establish a …model system for financial enterprise risk early warning management and intelligent real-time monitoring based on fuzzy theory. This article first collected a large amount of data through the literature investigation method, and made a systematic and complete introduction to the related theoretical concepts of fuzzy theory and financial risk early-warning management, has laid a sufficient theoretical foundation for the subsequent exploration of the application of fuzzy theory in financial enterprise risk early warning management and intelligent real-time systems; Then a fuzzy comprehensive evaluation method that combines the analytic hierarchy process and fuzzy evaluation method is proposed, taking a listed company mainly engaged in automobile sales in our province as a case, the company’s financial risk management and modeling experiment of the intelligent real-time system; Finally quoted specific cases again, used the fuzzy comprehensive evaluation method to carry out risk warning and evaluation on the PPP projects of private enterprises in our province, and concluded that the project risk score is between 20-60, which is meet the severe-medium range in the risk level. Research shows that the use of fuzzy theory and modern network technology can make more accurate warnings and assessments of potential and apparent risks of financial enterprises, greatly improving the safety of financial enterprise management and reducing the losses caused by various risks. Show more

Keywords: Fuzzy theory, financial enterprise, risk early warning management, intelligent real-time system, monitoring and prevention

DOI: 10.3233/JIFS-189441

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6017-6027, 2021

Authors: Song, Chunhuan | Qian, Fucai

Article Type: Research Article

Abstract: With its unique array arrangement, the detection system radar has both space diversity gain and waveform diversity gain, and is currently recognized as a stealth target buster. The detection system radar is applied to a high-speed moving platform. Using distributed cooperative detection technology, non-coherent fusion detection based on signals can further improve the detection of stealthy targets. Aiming at the high-speed motion radar signal processing algorithm, this paper mainly studies the following three aspects: the first content is the analysis of the waveform characteristics: the basic principles and characteristics of the radar are explained; then the three orthogonal waveforms commonly …used in the radar are introduced, including Stepwise frequency division chirp signal, quadrature phase coded signal and mixed-signal; the second content detects radar targets and analyzes the correlation between the scattering coefficients of different radar channels; for scenarios where the scattering coefficients between the channels are non-coherent Introduced two kinds of non-coherent fusion detectors based on generalized likelihood ratio algorithm: centralized detector and double threshold detector; the third content radar multi-target pairing is aimed at the problem of radar multi-target pairing with large inertial navigation error. A multi-target pairing algorithm that uses target delay information and combines the radar’s multi-channel information redundancy characteristics is presented. An expression for judging the correctness of target pairing is derived, and the target pairing steps are given. The relationship between the amount of algorithm operation and the number of radar stations and the number of targets is analyzed in conclusion. Show more

Keywords: High-speed motion platform, generalized likelihood ratio based, orthogonal waveform, non-coherent fusion detection

DOI: 10.3233/JIFS-189442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6029-6038, 2021

Authors: Yuan, Zhiqian | Jin, Chaoyang | Chen, Zhaojun

Article Type: Research Article

Abstract: In recent years, with the rapid development of computer technology, the need for barrier-free communication between people of all countries have become more and more urgent. Therefore, it is extremely important to establish a high translation accuracy and high-quality English translation system. At present, Although the various English translation systems on the market have solved the communication problems between different languages to a certain extent, there are a series of problems such as language translation ambiguity and inaccurate use of words in translation methods, in order to improve English The translation accuracy of the translation system can improve the quality …of the English translation system. This paper proposes a language analysis study of the English translation system based on fuzzy algorithms. The research of this paper firmly grasps the analysis and understanding of the language, analyzes it from the corpus, vocabulary, syntax, and translation characteristics, and fully understands its language characteristics, so as to eliminate the semantic understanding ambiguity in the translation process to a certain extent. Thereby improving the accuracy of the translation. The English translation system designed in this paper includes an image input module and an image recognition module, so the Gaussian blur algorithm is used for processing. The Gaussian blur algorithm can retain edge information in the edge area where the pixel value of the image changes sharply, and can effectively remove noise and enhance the image effect. Therefore, this article uses fuzzy algorithm-based English translation system language analysis research, first analyze the English language characteristics, and then use Gaussian fuzzy algorithm to denoise the image in the translation system, and then display the image recognition results. Show more

Keywords: English translation system, language analysis research, fuzzy algorithm

DOI: 10.3233/JIFS-189443

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6039-6047, 2021

Authors: Wang, Yingying | Zhang, Yongzhi

Article Type: Research Article

Abstract: Tennis is a set of sports and entertainment and a sports activity, since 2014, tennis in China has been another rapid development. With the development of economy and technology, tennis training mode has been further optimized and reformed. At present, tennis training robot is the mainstream way to train athletes. However, there are some defects in the current tennis training robots, such as the low accuracy of human motion real-time evaluation, and the lack of stability. Therefore, this paper puts forward the related research on the real-time evaluation algorithm of human motion in tennis training robots, hoping to make up …for the deficiency in this field. The research of this paper is mainly divided into four parts. The first part is to analyze the current situation of technology research in this field and put forward the idea of this paper by analyzing the shortcomings of the existing technology. The second part is the related basic theory research; this part deeply studies the core theory of tennis training and intelligent training robot, which provides a theoretical basis for the realization of the optimization scheme. The third part is the design and implementation of a real-time human motion evaluation optimization algorithm for tennis training robots. At the end of the paper, that is, the fourth part, through the way of field test and investigation, further proves the superiority of the improved real-time evaluation algorithm of human movement. The algorithm has good stability and accuracy and can meet the existing tennis training requirements. Show more

Keywords: Tennis training, artificial intelligence, intelligent robots, motion capture

DOI: 10.3233/JIFS-189444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6049-6057, 2021

Authors: Cheng, Yuan | Wang, Kunqian

Article Type: Research Article

Abstract: Small and medium-sized manufacturing enterprises have the characteristics of large numbers and small scales. Problems such as backward manufacturing technology, lack of talents, small amount of information resources, and insufficient product research and development capabilities have severely restricted the development of enterprises. The backward manufacturing design model cannot adapt to the development trend of modern manufacturing informatization. This paper proposes and designs a fuzzy inference model and fuzzy inference engine algorithm with threshold. In order to describe the numerical multiple input and multiple output variables in the industrial manufacturing design industry, the relevant experience is used to make numerical reasoning …decisions. Applying fuzzy sets and fuzzy theory to the expert system, a fuzzy rule model containing the membership function information and thresholds of the corresponding fuzzy sets is proposed and established, and a fuzzy reasoning system suitable for numerical and uncertain reasoning decisions is constructed. The improved grey relational analysis method is used to decompose and evaluate the exponential mathematical quantitative process of manufacturing enterprises. Based on the fuzzy Decision Analytic Network Process (DANP) method to calculate the relative weight of the influencing factors in the evaluation system, the evaluation index of the enterprise is obtained. Starting from the industrial manufacturing design process, this article constructs a relatively comprehensive and reasonable enterprise exponential mathematical quantitative process decomposition evaluation system. Considering that there are complex interactions between the various influencing factors in the system, the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method is selected to process the direct impact matrix of the evaluation system, and the causal relationship between the indicators is obtained. The fuzzy exponential gray correlation method is used to evaluate the quantitative process of industrial manufacturing design, avoiding the shortcomings of traditional methods that only consider ideal values. Show more

Keywords: Industrial manufacturing design, quantitative process decomposition, DANP, fuzzy reasoning

DOI: 10.3233/JIFS-189445

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6059-6068, 2021

Authors: Xie, Yun

Article Type: Research Article

Abstract: The urban rail transit power supply system is an important part of the urban power distribution network and the power source of the rail transit system. It is responsible for providing safe and reliable electrical energy to urban rail trains and power lighting equipment. This paper processes the obtained long-period rail transit power load learning sample data matrix, according to the principle of normalization processing, effectively eliminates irregular data in the sample set and fills in possible missing data, thereby eliminating bad data or fake data for model learning. Moreover, this avoids the generation of huge errors that cause exponential …growth in the model due to the increase in the learning sample size and the irregularity of the data. According to the characteristics of power load, this paper comprehensively considers the influence of temperature and date type on the maximum daily load, applies the fuzzy neural network model to the long-period load forecasting of long-period rail transit, and introduces the whole process of establishing the forecasting model in detail. Through detailed analysis of the actual data provided by the EUNITE network, the relevant factors affecting the daily maximum load were determined, and then the appropriate fuzzy input was selected to establish the corresponding fuzzy neural network prediction model, and a relatively ideal prediction result was obtained. The experimental results fully proved the great potential of fuzzy neural network in long-term power load forecasting. Show more

Keywords: Power load forecasting, fuzzy neural network, fuzzy logic, rail transit

DOI: 10.3233/JIFS-189446

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6069-6079, 2021

Authors: Wang, Ruijuan | Zhuo, Wei

Article Type: Research Article

Abstract: The image intelligent processing analysis technology uses a computer to imitate and execute some intellectual functions of the human brain, and realizes an image processing system with artificial intelligence, that is, an image processing analysis technology is an understanding of an image. The degree of intelligent automated analysis and processing is low, many operations need to be done manually, causing human error, inaccurate detection, and time-consuming and laborious. Deep learning method can extract features step by step in the original image from the bottom to the top. Therefore, based on feature analysis technology, this paper uses the deep learning method …to intelligently and automatically analyse the visual image. This method only needs to send the image into the system, and then the manual analysis is not needed, and the analysis result of the final image can be obtained. The process is completely intelligent and automatically processed. First, improve the deep learning model and use massive image data to choose and optimize parameters. Results indicate that our method not only automatically derives the semantic information of the image, but also accurately understands the image accurately and improve the work efficiency. Show more

Keywords: Image intelligent, automatic processing analysis, deep learning

DOI: 10.3233/JIFS-189447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6081-6090, 2021

Authors: Liu, Chen | Sergeevna, Chernova Oksana

Article Type: Research Article

Abstract: With the development of science and technology, in the field of oilfield commissioning, the requirements for process management are more and more standardized and scientific, and the requirements for decentralized equipment status detection and maintenance are also higher and higher. It is the hope of any manager to eliminate hidden dangers and prevent them in a timely manner. This paper introduces an intelligent debugging model based on big data. Based on the big data mechanism, the model is divided into different functions according to different functions and requirements. It can ensure the authenticity of debugging data, coordinate all big data …work through the big data communication mechanism, and conduct scientific management of debugging data. The model is divided into three levels: data acquisition layer, data transmission layer and control management layer. The offshore oil intelligent debugging platform software based on big data technology is built. A new intelligent debugging method for offshore oil based on big data is presented to study the warning information, fault location and equipment health status of intelligent debugging. Development for Marine oil intelligent debugging applications, for business people to provide intelligent Marine oil intelligent debugging method, provide data support for management decision-making, implementation of the lean management data in the field of intelligent debugging, improving the capacity of intelligent debugging data analysis and mining, effective use of the existing intelligent debugging automation system and other related data in the system, solved the “huge amounts of data, information, the lack of a” awkward situation, improve intelligence debugging application function, meet the demand of intelligent debugging of each department, improve the efficiency of debugging and running reliability and intelligent management. Show more

Keywords: Intelligent debugging, offshore oil, big data, communication mechanism

DOI: 10.3233/JIFS-189448

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6091-6101, 2021

Authors: Ruan, Kun | Li, Yuan

Article Type: Research Article

Abstract: Using the theoretical knowledge of ergonomics, physiology, and psychology, carried out the humanized design of human body adaptive sports equipment; using the theoretical knowledge of modeling, color, material science and other related disciplines, proposed the human body adaptive sports equipment Humanized design method. Aiming at the fuzziness of the industrial design of human adaptive sports equipment, fuzzy mathematics theory is used as an analysis tool, combined with the actual characteristics of the industrial design of human adaptive sports equipment, focusing on the nature of industrial design under fuzzy theory. Comprehensive analysis and understanding of design-related factors, and the introduction of …expert survey method in the case of no basic data source in innovative design, to obtain the weight value of single factor influence, this will help designers grasp the main contradiction, achieve a targeted, and Solve key problems with higher efficiency. Subsequent use of fuzzy mathematics tools to put forward a quantitative index for the selection of options, which will help analyze the pros and cons of the various options, so as to provide a reliable reference for decision makers. This method makes up for the shortcomings of traditional methods in the process of design factor analysis and program selection. Show more

Keywords: Human body adaptation, sports equipment, industrial design, fuzzy mathematics

DOI: 10.3233/JIFS-189449

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6103-6112, 2021

Authors: Xu, Xia

Article Type: Research Article

Abstract: The current network environment is dynamic, open and extensible. In order to better ensure the needs of users, higher requirements are placed on link resource allocation. Based on the research and analysis of the instant communication protocol, this paper studies an intelligent routing evolution algorithm and related fault recovery strategy for the instant communication network. Research on instant messaging intelligent algorithms for routing evolution is mainly based on routing algorithms and artificial intelligence intelligent algorithms. When a link failure occurs in the communication network, the routing algorithm performs route reconstruction and optimization on the entire instant communication network. Considering that …there may be evolutionary needs of large-scale routing networks in practical applications, this paper introduces artificial intelligence intelligent algorithms to optimize intelligent algorithms to improve efficiency. A cognitive routing protocol based on MIMO (Multiple Input Multiple Output) technology is proposed. By using MIMO technology, a lot of gain is brought to the communication link under multiple antennas. These gains correspond to different link types. The protocol realizes cognition through intelligent routing evolution algorithm and predicts the state of the network. Setting the routing life and hello period according to the perceived network status can optimize the performance of the network. Show more

Keywords: Instant messaging, network link optimization, intelligent routing evolution algorithm, CRMA routing protocol

DOI: 10.3233/JIFS-189450

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6113-6124, 2021

Authors: Sun, Tingting | Lv, Xingjun | Cai, Yakun | Pan, Yuqing | Huang, Jianchang

Article Type: Research Article

Abstract: The thesis starts with the connotation and attributes of software testing quality, introduces software testing quality evaluation methods, and analyzes and discusses software testing quality evaluation models based on fuzzy mathematics theory. Focusing on the key technical problems of software testing quality, discuss the key technologies to solve the software testing quality evaluation model establishment. Through the use of fuzzy models, the cost of software testing quality evaluation is effectively reduced, and the reliability of software testing quality evaluation methods is improved. This model can quickly evaluate the quality of software testing, can avoid the occurrence of local maxima, overcome …the shortcomings of existing evaluation models and tools, and can correctly reflect the relationship between the internal and external properties of the software. Using the new software testing quality evaluation method, comparing the evaluation models and tools used before, summarizing the methods of software testing quality improvement. The application of these methods effectively improves the software testing quality. Show more

Keywords: Fuzzy mathematics, fuzzy evaluation, software quality, test quality

DOI: 10.3233/JIFS-189451

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6125-6135, 2021

Authors: Cao, Ning | Miao, Xiaoming | Zhang, Juan

Article Type: Research Article

Abstract: With the development of information technology and the reduction of storage equipment costs, a large number of databases have been able to create and store massive amounts of data. How to use this data to provide guidance and advice for business decisions is a difficult problem that decision analysis systems need to solve. This paper designs a new multi-dimensional heterogeneous network information model, defines the binary relational meta-path in the heterogeneous network and the n-ary relational meta-path, and studies the relationship of these meta-paths as a new way to guide network aggregation. An intelligent emergency decision support system based on …the GIS platform and the concept of the plan library was established. The system adopts the method of artificial intelligence and GIS technology to complete the management, analysis and processing of map space data, and realizes the rapid and automatic generation of emergency decision-making. Finally, through experiments on large-scale real and simulated data, it is verified that the system can effectively and efficiently analyze large-scale multi-dimensional heterogeneous networks. Show more

Keywords: Multidimensional network, heterogeneous information network, spatial intelligent decision system, rapid decision

DOI: 10.3233/JIFS-189452

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6137-6149, 2021

Authors: Zheng, Yi

Article Type: Research Article

Abstract: In this paper, an in-depth analysis of automated production line faults based on fuzzy algorithms is carried out and based on an in-depth investigation of the mechanism of equipment faults, research work on equipment state prediction and production line fault diagnosis is carried out, and the corresponding algorithm model workflow is given, which has some practical application value for improving the accuracy of production line fault prediction. The algorithm with data mining association rules is proposed to extract the confidence parameters of the conditional state fuzzy net model, and an inverse conditional state fuzzy net is established based on the …conditional state fuzzy net for fault diagnosis and reasoning, and a dynamic confidence level reasoning mechanism is also established for reverse reasoning based on the iterative algorithm of maximum algebra. To monitor the operating status of the production line more intuitively, a production line fault prediction and analysis system is developed based on the platform, which mainly includes a data management module, state monitoring module, state prediction module, fault diagnosis module, and maintenance advice module, which can more easily realize the monitoring of the production line equipment state and fault early warning prompting, making the system more practical value. Show more

Keywords: Fuzzy algorithms, automation, production lines, failure analysis

DOI: 10.3233/JIFS-189453

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6151-6162, 2021

Authors: Li, Qian | Li, Shuyuan

Article Type: Research Article

Abstract: Aiming at the precocious convergence, low search accuracy and easy divergence of most particle swarm optimizations with velocity terms, a particle swarm optimization (IWPSO) with random inertia weights and quantization is proposed. First, the inertia weights are obeyed to be distributed randomly, and the learning factors are adjusted asynchronously to optimize the parameters in BP network. Secondly, BP network is trained using the IWPSO algorithm based on the sample data. Finally, simulation experiments prove that the algorithm has significantly improved search speed, convergence accuracy, and stability compared with existing improved algorithms. Due to the characteristics of IWPSO algorithm, the BP …neural network optimized by IWPSO has better global convergence performance and is an efficient particle swarm optimization. Show more

Keywords: Optimization, artificial neural network, swarm intelligence algorithm

DOI: 10.3233/JIFS-189454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6163-6173, 2021

Authors: Fang, Zhichun | Zhu, Zhengguo | Chen, Xinyu

Article Type: Research Article

Abstract: The construction of tunnels is often long and deep buried tunnels, and the geological conditions are more complex. Based on Jianshan tunnel in Gansu Province, the special geological conditions such as high ground stress and weak interbedded surrounding rock make the excavation of tunnel easy to produce large deformation. In this article, the software finite difference software FLAC3D was used to establish numerical models and select the best construction method by comparing the deformation of the tunnel under different construction methods. Aiming at the deformation characteristics of soft rock tunnels in highland interbedded layers, the control measures of tunnel deformation …are discussed. Mainly consider the two aspects of the bolt support plan and the second lining construction time, comprehensively compare the deformation characteristics of the tunnel, and select the best working condition. The research results show that the combination of three-step temporary invert method and three-step ultra short bench method is recommended for the tunnel construction; when the bench length is 4 m, the deformation control effect of the tunnel is the best; by improving the length and angle of the anchor rod, the deformation of the tunnel can also be well controlled. Show more

Keywords: High ground stress, interbedded soft rock, construction technology, deformation control

DOI: 10.3233/JIFS-189455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6175-6183, 2021

Authors: Shao, Mengliang | Qi, Deyu | Xue, Huili

Article Type: Research Article

Abstract: Outlier detection is an important branch of data mining. This paper proposes an advanced fast density peak outlier detection algorithm based on the characteristics of big data. The algorithm is an outlier detection method based on the improved density peak clustering algorithm. This paper improves the original algorithm. From the perspective of outlier detection, although it is a clustering idea, it avoids the clustering process, reduces the time complexity of the cluster-based outlier detection algorithm, and absorbs. The outlier detection based on neighbors is not sensitive to data dimensions and other advantages. In the power industry, outlier detection can be …used in areas such as grid fault detection, equipment fault detection, and power abnormality detection. The simulation experiment of outlier detection based on the daily load curve of single and multiple transformers in a certain province shows that the improved algorithm can effectively detect outliers in the data. Show more

Keywords: Outlier detection, big data, KNN algorithm, density clustering

DOI: 10.3233/JIFS-189456

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6185-6194, 2021

Authors: Yu, Hui | Hu, Lingyan

Article Type: Research Article

Abstract: Usually the highlights can be calculated with the specular term of the bidirectional reflectance distribution functions developed for glossy or matte materials. However, as for the translucent materials, complex appearance could be caused by the scattering of light inside the medium. An efficient highlight generation model is presented to simulate the highlight effects on smooth or rough surfaces or around the boundaries of objects made from translucent materials. The presented model is derived from the directional dipole model approximation of the diffusive part of the bidirectional scattering surface reflectance distribution function. Unlike the previous specular reflection models, the presented model …builds a relationship between the highlights and the scattered lights inside the medium by considering the refracted ray of the incident point and the ray toward the emergent point, which could represent the variation in fluence due to the internal scattering at the surface. By integrating a rendering process with the directional dipole model, the resulting highlight effects term could be represented in a similar way by the specular term of a bidirectional reflectance distribution function model. The number and the strength of the generated highlight pixels were compared among typical highlight generation models. It is demonstrated that the presented model could generate highlight effects at the appropriate positions and enhance the perceptual translucency of specific edge areas greatly. Show more

Keywords: Highlights, bidirectional scattering surface reflectance distribution function, bidirectional reflectance distribution function, directional dipole, subsurface scattering, translucency appearance

DOI: 10.3233/JIFS-189457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6195-6204, 2021

Authors: Li, Wenguang | Feng, Guosheng | Jia, Sumei

Article Type: Research Article

Abstract: This paper studies a hybrid power system composed of fuel cells, super capacitors and batteries. Super capacitors are used as auxiliary energy sources to provide the required high power when the car starts and accelerate, while absorbing braking energy when the car is braking. Fuzzy control is used to optimize its energy management strategy. The fuzzy controller of the three-energy source system takes the battery, super capacitor, and bus demand power as the input of the fuzzy controller, and the battery demand power and the fuel cell demand power as the fuzzy controller output. The system realizes the energy distribution …of super capacitors, fuel cells and storage batteries according to power requirements, thereby improving the performance of the system and extending the life of components. And with hydrogen consumption as the optimization goal, the particle swarm algorithm is used to optimize the parameters of the fuzzy membership function. Compared with the fuzzy control strategy without particle swarm optimization, the optimized fuzzy energy management strategy reduces the hydrogen consumption of fuel cell vehicles. 10 L/(100 km)-1, which improves the economy of the vehicle. Show more

Keywords: Fuel cell vehicles, hybrid powertrain, energy management strategy, fuzzy control, particle swarm optimization

DOI: 10.3233/JIFS-189458

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6205-6217, 2021

Authors: Zhu, Yu | Liu, Xiantao

Article Type: Research Article

Abstract: In this paper, an in-depth study on the quantification of influencing factors and big data visualization of key monitoring indicators in the refined oil products market is carried out through fuzzy mathematical methods, and a system for quantifying influencing factors and big data visualization of key monitoring indicators in the refined oil products market with the fuzzy mathematical background is designed and implemented. The system realizes the functions of flow visualization, attack visualization, target tracking visualization, etc., and optimizes the system from the perspectives of performance and visualization effect. It achieves the display and interaction of multi-dimensional data in space …and time with multiple views, angles, and dimensions. Data tagging and data correlation for key aspects of the product production process are realized through fuzzy mathematics and other means, and a quality traceability system for the manufacturing industry is realized on this basis, through which the data of some key stages of the product production process can be displayed retrospectively. The study proves that the business model of refined oil logistics platform based on value network can significantly improve the user’s perceived value and benefit all parties within the value network, realizing the complementary advantages of refined oil production enterprises and logistics platform companies, improving the efficiency of enterprise’s logistics and maximizing the profit of each subject within the value network to achieve profitability for all parties. Show more

Keywords: Fuzzy mathematics, refined products market, quantification of influences, key monitoring indicators, big data visualization

DOI: 10.3233/JIFS-189459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6219-6229, 2021

Authors: Tian, Hui | Zhang, Zhujun | Yuan, Zhihua | Liu, Xiaochan | Qi, Yuyan | Wang, Zhenguo | Wang, Liang

Article Type: Research Article

Abstract: In view of the problems of low stiffness, small driving force and large balloon effect existing in the current soft actuator, this paper proposes an optimization method to enhance the overall stiffness of the soft gripper by using rigid components based on the multi-cavity soft pneumatic actuator. This paper introduces the main components of the actuator: the soft part poured by liquid silica gel, and the open rectangular rigid structures by 3D printed. The kinematics model of the finger is established based on the Piecewise Constant Curvature model(PCC). The bending performance of the enhanced stiffness gripper is verified by finite …element analysis(FEA): the tip force of actuator increased with the increase of the number of rigid structures when the bending angle is constant. According to the and experimental data, the overall stiffness of soft gripper is increased by the rigid structure without affecting the flexibility of operation. And the maximum weight which can grasp is 3.4 times that of the traditional soft gripper, improved the grasping range of the soft gripper effectively. Show more

Keywords: Soft gripper, stiffness-enhanced, PCC model, FEA

DOI: 10.3233/JIFS-189460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6231-6238, 2021

Authors: Wang, Yu | Lian, Zhengmei | Zou, Jihua

Article Type: Research Article

Abstract: The main reason that hinders early treatment of ACS patients is delayed patient decision-making (PD). In order to explore the delay factors of patients with ACS, this paper builds a machine learning-based analysis model of delay factors for patients with acute coronary syndrome based on machine learning. Moreover, this paper combines structural equations to analyze the factors affecting accidents, and uses the generalized ordered logit model in statistics and the popular random forest model in machine learning to establish the analysis models of the delay factors of acute coronary syndromes, and analyze the functional structure of the models. In addition, …this paper obtains data through actual survey methods, and analyzes the data through the model constructed in this paper to explore the risk factors that affect the delay in seeking medical treatment, which is presented through charts. The research results show that the model constructed in this paper is more reliable and can be applied in practice. Show more

Keywords: Machine learning, mountain area, acute coronary syndrome, delay in seeking medical treatment, factor analysis

DOI: 10.3233/JIFS-189461

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6239-6250, 2021

Authors: Huang, Yan

Article Type: Research Article

Abstract: Enterprise marketing is affected by a variety of factors, which lead to certain fluctuations in corporate market influence, and it is difficult to effectively control the elasticity of market influence. In order to improve the elastic analysis effect of enterprise marketing investment, based on the machine learning algorithm, this paper uses the equilibrium movement model to construct an intelligent model suitable for marketing simulation analysis. The equilibrium movement model used in this paper is a simulation of a real situation, which can be used for predictive analysis and can measure how much an exogenous impact can cause endogenous variables to …change. Moreover, this paper establishes a mathematical model to express the influence of marketing with the help of producer surplus, quantify this influence, and use numbers to show the influence of marketing more intuitively. In addition, this paper uses case analysis to study the effect of model analysis. From the research process and conclusions, it can be seen that the model constructed in this paper has certain effects. Show more

Keywords: Balanced mobility model, marketing, investment, elasticity analysis

DOI: 10.3233/JIFS-189462

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6251-6261, 2021

Authors: Zhu, Bin | Zhou, Jie

Article Type: Research Article

Abstract: In order to build a virtual urban planning model and improve the effect of urban planning, this paper builds a virtual urban planning design model based on GIS big data technology and machine learning algorithms, and proposes a solution that combines multiple features. With the development of polarized SAR in the direction of high resolution, a single feature often cannot fully express the detailed information of ground objects, resulting in poor classification results and low accuracy. The combination of multiple features can express feature information well. In addition, this paper uses the ELM method to plan SAR ground object classification, …uses an extreme learning machine classification algorithm with fast learning speed and good classification effect, and uses ELM as a classifier. Finally, this paper designs experiments to explore the performance of the model constructed in this paper from two aspects: detection accuracy and planning score. The research results show that the model constructed in this paper meets the expected goals. Show more

Keywords: GIS, big data, machine learning, urban planning

DOI: 10.3233/JIFS-189463

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6263-6273, 2021

Authors: Jiang, Zhiqi | Wang, Xidong

Article Type: Research Article

Abstract: This paper conducts in-depth research and analysis on the commonly used models in the simulation process of air pollutant diffusion. Combining with the actual needs of air pollution, this paper builds an air pollution system model based on neural network based on neural network algorithm, and proposes an image classification method based on deep learning and Gaussian aggregation coding. Moreover, this paper proposes a Gaussian aggregation coding layer to encode image features extracted by deep convolutional neural networks. Learn a fixed-size dictionary to represent the features of the image for final classification. In addition, this paper constructs an air pollution …monitoring system based on the actual needs of the air system. Finally, this article designs a controlled experiment to verify the model proposed in this article, uses mathematical statistics to process data, and scientifically analyze the statistical results. The research results show that the model constructed in this paper has a certain effect. Show more

Keywords: Neural network, machine learning, air pollution, intelligent monitoring

DOI: 10.3233/JIFS-189464

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6275-6285, 2021

Authors: Xiaohui, Chen | Xi, Yang | Haoyuan, Pang | Yongjian, Ou

Article Type: Research Article

Abstract: This article discusses the design and implementation of a 100 G tunable laser optical module, and briefly introduces the functions of each module in the MCU. The main technologies involve TEC control, wavelength locking, wavelength tuning, and power compensation. By analyzing the traditional positional proportional integral and differential algorithm, improving the proportional integral and differential algorithm, and using the algorithm to achieve wavelength locking, this can prevent the wavelength drift or even the lock due to the overload of the adjustment during the system adjustment process.

Keywords: PID, wavelength locking, tunable laser, TEC

DOI: 10.3233/JIFS-189465

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6287-6294, 2021

Authors: Chen, Yuan

Article Type: Research Article

Abstract: The macro traffic flow model of expressway is transformed into a general discrete-time nonlinear system model including this model by using the repeatability of the macro traffic flow model, and then a parameter identification algorithm based on iterative learning is designed for this general discrete-time nonlinear system model. The convergence of this parameter identification scheme is proved by strict theoretical derivation and robustness. Simulation results verify the effectiveness of the algorithm.

Keywords: Macro traffic flow model, iterative learning control, parameter identification

DOI: 10.3233/JIFS-189466

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6295-6303, 2021

Authors: Xiong, Cheng | Li, You | Long, Nuoya

Article Type: Research Article

Abstract: Based on the introduction of the principle of the optical wireless system, the WDM-ROF based on hybrid modulation of MZM and OFM is designed WDM-ROF-PON system architecture, using simulation software to build the system to verify the rationality of the MZM and OFM hybrid modulation system structure; and put forward an MZM and OFM hybrid modulation scheme, using IRZ code in the downlink data stream, with better extinction ratio and dispersion tolerance, reducing the cost of the user receiving equipment, improving the system transmission quality. The simulation results show that the scheme of MZM and OFM hybrid modulation WDM-of-pon network …architecture is reasonable and practical. Show more

Keywords: MZM and OFM hybrid modulation, WDM-PON, ROF

DOI: 10.3233/JIFS-189467

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6305-6313, 2021

Authors: Ma, Xiaona

Article Type: Research Article

Abstract: English text is difficult to recognize under the interference of blurred background, so it is necessary to improve the fixed-point tracking technology of English text. Based on machine learning algorithms, this paper studies the fixed-point tracking model of English reading text based on mean shift and multi-feature fusion. The target tracking algorithm based on mean shift obtains the description of the target model and the candidate model by calculating the pixel feature probability in the target area and the candidate area. Then, it uses the similarity function to measure the similarity between the initial frame target model and the current …candidate model, selects the candidate model that maximizes the similarity function, and obtains the target model mean offset vector. Finally, it continuously iteratively calculates the offset vector based on this vector, and finally converges to the true position of the target, thereby achieving the effect of tracking. In general, it is verified that the model constructed in this paper works well through control experiments. Show more

Keywords: Machine learning, mean shift, multi-feature fusion, English reading, fixed-point tracking

DOI: 10.3233/JIFS-189468

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6315-6325, 2021

Authors: Song, Xin

Article Type: Research Article

Abstract: The difficulty of obtaining the characteristics of the corpus database of neural machine translation is a factor hindering its development. In order to improve the effect of English intelligent translation, based on the machine learning algorithm, this paper improves the multi-objective optimization algorithm to construct a model based on the English intelligent translation system. Moreover, this paper uses parallel corpus and monolingual corpus for model training and uses semi-supervised neural machine translation method to analyze the data processing path in detail and focuses on the analysis of node distribution and data processing flow. In addition, this paper introduces data-related regularization …items through the probabilistic nature of the neural machine translation model and applies it to the monolingual corpus to help the training of the neural machine translation model. Finally, this paper designs experiments to verify the performance of this model. The research results show that the translation model constructed in this paper is highly intelligent and can meet actual translation needs. Show more

Keywords: Improved algorithm, machine learning, multi-objective optimization algorithm, English translation

DOI: 10.3233/JIFS-189469

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6327-6337, 2021

Authors: Zhao, Chao | Yang, Hongling | Li, Xiaoqian | Li, Rui | Zheng, Shoucun

Article Type: Research Article

Abstract: The intelligent scheduling algorithm for hierarchical data migration is a key issue in data management. Mass media content platforms and the discovery of content object usage patterns is the basic schedule of data migration. We add QPop, the dimensionality reduction result of media content usage logs, as content objects for discovering usage patterns. On this basis, a clustering algorithm QPop is proposed to increase the time segmentation, thereby improving the mining performance. We hired the standard C-means algorithm as the clustering core and used segmentation to conduct an experimental mining process to collect the ted QPop increments in practical applications. …The results show that the improved algorithm has good robustness in cluster cohesion and other indicators, slightly better than the basic model. Show more

Keywords: Fuzzy clustering algorithm, membership, martial arts video, image segmentation, intersection clustering, object extraction

DOI: 10.3233/JIFS-189470

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6339-6347, 2021

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6349-6349, 2021

Authors: Ramachandran, Varatharajan

Article Type: Editorial

Abstract: This special issue of the Journal of Intelligent & Fuzzy Systems contains selected articles of Fuzzy model for human autonomous computing in extreme surveillance and it’s applications

DOI: 10.3233/JIFS-189475

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6351-6353, 2021

Authors: Lalitha, S.

Article Type: Research Article

Abstract: Cancer has been one of the most serious health challenges to the human kind for a long period of time. Lung cancer is the most prevalent type of cancer which shows higher death rates. However, lung cancer mortality rates can be tracked by periodic screening. With the advanced medical science, the society has reaped numerous benefits with respect to screening equipments. Computed Tomography (CT) is one of the popular imaging techniques and this work utilizes the CT images for lung cancer detection. An early detection of lung cancer could prolong the lifetime of the patient and is made effortless by …the latest screening technology. Additionally, the accuracy of disease detection can be enhanced with the help of the automated systems, which could support the healthcare experts in effective diagnosis. This article presents an automated lung cancer detection system equipped with machine learning algorithm, which can differentiate between the benign, malignant and normal classes of lung cancer. The accuracy of the proposed lung cancer detection method is around 98.7%, which is superior to the compared approaches. Show more

Keywords: Cancer, Lung cancer detection, CT images, machine learning

DOI: 10.3233/JIFS-189476

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6355-6364, 2021