Journal of Intelligent & Fuzzy Systems - Volume 39, issue 4

Authors: Chen, Feng | Wang, Chengyue

Article Type: Research Article

Abstract: The rapid development of computers makes people’s production and life rich and colorful, and people communicate with each other in the world of the Internet. The daily downloads and uploads of network pictures are countless. The existing image recognition technology alone cannot meet the currently required functions, so technology is needed to meet the retrieval requirements. The purpose of this paper is to study the image recognition technology based on the computer platform. This paper takes vehicle image recognition as an example. By performing a deblurring operation on the vehicle image, the edge detection method is used to separate the …target vehicle image from the background, and the image is binary. Processing. Based on different eigenvalue categories, intelligent recognition of vehicle models is achieved through Bayesian classifiers. Collect experimental data through simulation experiments. Experimental data shows that after a certain number of nodes, the recognition efficiency is higher than the image recognition technology running on a stand-alone platform. The experimental data show that the image recognition technology based on a cloud computing platform is conducive to the development of image recognition technology. It can quickly solve the problems of traditional image detection systems in terms of computing efficiency and data processing ability, and has guiding significance for the development of image recognition technology. Show more

Keywords: Cloud computer, image recognition, edge detection method, recognition efficiency

DOI: 10.3233/JIFS-179997

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5119-5129, 2020

Authors: Qi, Wanqiang

Article Type: Research Article

Abstract: The main reason that currently hinders the commercialization of electric vehicles is a bottleneck in battery, motor and electronic control technology, however, an In-depth study of electronic control technology is one of the most effective means to break through this bottleneck at present. The purpose of this paper is to solve the problem that the pure electric vehicle is difficult to meet the driver’s acceleration intention in the urban road cycle acceleration work condition and the brake energy recovery process does not consider the battery state of charge during the deceleration work condition. Proposed a control strategy that can meet …the requirements of road cycle conditions and driver’s driving intentions and take account of the vehicle operating status. Use a fuzzy control algorithm to develop a fuzzy controller that taking the motor demand speed change rate and battery state of charge as input, the motor demand torque compensation coefficient as output. The experimental results show that the modified control strategy can improve the actual output power, the actual output torque of the motor and actual driving force of the wheel under the premise of maintaining economy; it also improved the acceleration performance and climbing performance of pure electric vehicles, and can recycle braking energy efficiently. The experimental results show that the secondary development control strategy can meet the requirements of the cycle work condition CYC_ECE_EUDC for the speed and driving force and the driver’s driving intention under the premise of not sacrificing economics. Show more

Keywords: Pure electric vehicle, driving intention, fuzzy control strategy, driver PID model

DOI: 10.3233/JIFS-179998

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5131-5139, 2020

Authors: Li, Yingjie | Chen, Lianjun

Article Type: Research Article

Abstract: To reduce the resource and energy waste of colleges and universities more accurately and efficiently, this paper has developed a smart classroom data analysis system based on the Internet of Things, which realizes a variety of sensor information (temperature, humidity, smoke). Environmental parameters such as carbon dioxide concentration and light intensity), remote collection of equipment information, data storage and data analysis functions, and intelligent control of smart classrooms. Data analysis uses an improved LSTM model to predict energy consumption. The model uses LSTM and bidirectional LSTM and uses the ELU activation function instead of the sigmoid and tanh activation functions …of the LSTM. Compared with the standard LSTM model and the LSTM model without the ELU activation function, the model improves the prediction accuracy, better avoid the gradient disappearance, and reduces the over-fitting. The system implementation results show that the system can effectively reduce school energy waste. Show more

Keywords: Internet of things, smart classroom, data analysis, Bi-LSTM

DOI: 10.3233/JIFS-179999

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5141-5148, 2020

Authors: Liu, Kainan | Zhang, Meiyun | Hassan, Mohammed K.

Article Type: Research Article

Abstract: To monitor the scene anomaly in real-time through video and image and identify the emergencies, try to respond quickly at the beginning of the emergency and reduce the loss. This paper mainly focuses on the realization of the image recognition system for the anomalous characteristics of tourism emergencies. The problem is to study the number of people in the scenic spot based on scenic spot monitoring. The video-based population anomaly monitoring method has improved the AUC index of the W-SFM method by 0.423, and the AUC has increased by 0.0844 compared with the optical flow method; Degree-enhanced algorithm (BCOF), by …grasping the micro-blog data related to the scenic spot, comprehensively predicts the overall comfort of the current tourists in the scenic spot, and establishes a tourist state expression model. Compared with the BN algorithm and the NEG algorithm, the BCOF algorithm is the accuracy and the recall rate of tourists in the scenic spots was improved by 14% and 18% respectively. The image recognition system of tourism emergency anomaly was established, and the early warning model of tourism emergency based on group intelligence perception was used to implement early warning on scenic spots. Monitoring, can achieve an overall accuracy of 83.33%, the model has a strong predictive ability, and achieves a scenic spot Real-time monitoring of events. Show more

Keywords: Tourist scenic spot, image recognition, video recognition, emotional comfort, crowd anomaly monitoring, early warning model

DOI: 10.3233/JIFS-189000

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5149-5159, 2020

Authors: He, Zhenxiang | Li, Zhenjiang | Zhang, Shengcai | Lu, Jun

Article Type: Research Article

Abstract: In cloud data centers, different virtual machine placement strategies will affect the resource utilization efficiency of the whole system. How to improve the overall resource utilization of the system by adjusting the virtual machine placement strategy under limited resources is the focus of current researchers. In this paper, a new virtual machine placement strategy is proposed, which is based on the comprehensive constraints of various system resources. In the process of solving the problem, a multi-objective ant colony optimization algorithm is used. Simulation results show that this method can effectively reduce the number of physical machines activated in the data …center, and the accuracy is high. Show more

Keywords: Cloud data center, virtual machine placement, multiple resources constraints, ant colony optimization

DOI: 10.3233/JIFS-189001

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5161-5170, 2020

Authors: Xie, Chao | Xiao, Xiaoyong | Hassan, Dina K.

Article Type: Research Article

Abstract: Social media has accumulated a large number of users by its community, which has greatly changed and affected people’s lifestyles. Social media not only provides convenience for users to make friends, entertainment, information acquisition and other activities, but also provides an ideal way for the development of e-commerce with the advantages of fast transmission speed and accurate audience. The content and behavior of social e-commerce platforms are mostly generated and dominated by users, who are the key subjects that determine the development of platforms and the profitability of enterprises. The main purpose of this study is to enrich the theoretical …system of data mining for social e-commerce users and provide a theoretical basis and reference for platform and business management and operation of social e-commerce. First, based on the information ecology and information dissemination perspective, this paper constructs the model of information flow in social e-commerce. Second, based on the social network analysis method, analyzes the social network of social e-commerce users; Finally, based on the integrated model of technology acceptance and use (UTAUT), the theory of perceived risk and the theory of trust, the conceptual model of influencing factors of initial information adoption by users of social e-commerce is constructed, and the key influencing factors are identified by using Delphi method and DEMATEL method. The experimental results show that the degree of centrality of the new technology application is the largest, 5.250, which is the key factor influencing the initial information adoption of social e-commerce users. User satisfaction has the largest influence on the continuous information adoption intention of social e-commerce users, with the influence factor reaching 1.223, followed by IT self-efficacy (0.948), user relationship network structure (0.771), social e-commerce platform quality (0.637), perceived usefulness (0.419) and emotional attachment intensity (0.409). Show more

Keywords: Internet of things and big data, social e-commerce, data mining, user data

DOI: 10.3233/JIFS-189002

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5171-5181, 2020

Authors: Fan, Mingming | Li, Yunsong

Article Type: Research Article

Abstract: The purpose of this paper is to improve the existing computer graphics image processing technology, so that designers can produce more inspiration, improve the author’s ability to innovate. Based on the information in the field of graphics visual communication as the research object, through the elaboration of graphical information characteristics, development course, and the visual communication of computer graphical related, such as cognitive psychology, semiology theory research, analyzes the computer graphics into a kind of economic and effective way of conveying information, the significance of interface design for mobile media. Experiments demonstrate the unique advantages of graphics in the process …of information transmission. In 2022, the market size of computer graphics and vision will expand to 755.5 million RMB. It can be known that the communication mode integrating information and graphics, as the future development trend, will also be applied to more fields and play a greater role. Show more

Keywords: Computer graphics, graphics processing technology, visual communication, graphics design

DOI: 10.3233/JIFS-189003

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5183-5191, 2020

Authors: Zhang, Shiyi | Zhang, Laigang | Zhao, Teng | Selim, Mahmoud Mohamed

Article Type: Research Article

Abstract: Aiming at the characteristics of time-frequency analysis of unsteady vibration signals, this paper proposes a method based on time-frequency image feature extraction, which combines non-downsampling contour wave transform and local binary mode LBP (Local Binary Pattern) to extract the features of time-frequency image faults. SVM is used for classification and recognition. Finally, the method is verified by simulation data. The results show that the classification accuracy of the method reaches 98.33%, and the extracted texture features are relatively stable. Also, the method is compared with the other 3 feature extraction methods. The results also show that the classification effect of …the method is better than that of the traditional feature extraction method. Show more

Keywords: Time-frequency image, rotating machinery, fault diagnosis

DOI: 10.3233/JIFS-189004

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5193-5200, 2020

Authors: Liu, Bingjie | Zhu, Li | Ren, Jianlan

Article Type: Research Article

Abstract: Optimization algorithms have been rapidly promoted and applied in many engineering fields, such as system control, artificial intelligence, pattern recognition, computer engineering, etc.; achieving optimization in the production process has an important role in improving production efficiency and efficiency and saving resources. At the same time, the theoretical research of optimization methods also plays an important role in improving the performance of the algorithm, widening the application field of the algorithm, and improving the algorithm system. Based on the above background, the purpose of this paper is to apply the intelligent optimization algorithm based on grid technology platform to research. …This article first briefly introduced the grid computing platform and optimization algorithms; then, through the two application examples of the TSP problem and the Hammerstein model recognition problem, the common intelligent optimization algorithms are introduced in detail. Introduction: Algorithm description, algorithm implementation, case analysis, algorithm evaluation and algorithm improvement. This paper also applies the GDE algorithm to solve the reactive power optimization problems of the IEEE14 node, IEEE30 node and IEEE57 node. The experimental results show that the minimum network loss of the three systems obtained by the GDE algorithm is 12.348161, 16.348152, and 23.645213, indicating that the GDE algorithm is an effective algorithm for solving the reactive power optimization problem of power systems. Show more

Keywords: Grid computing platform, intelligent optimization algorithm, TSP problem, hammerstein model, simulated annealing algorithm

DOI: 10.3233/JIFS-189005

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5201-5211, 2020

Authors: Wang, Guangtong | Miao, Jianchun

Article Type: Research Article

Abstract: The economic interaction between the countries of the world is gradually strengthening. Among them, the US stock market is a “barometer” of the global economy, which has a huge impact on the global economy. Therefore, it is of great significance to study the data in the US stock market, especially the data mining algorithm of abnormal data. At present, although data mining technology has achieved many research results in the financial field, it has not formed a good research system for time series data in stock market anomalies. According to the actual performance and data characteristics of the stock market …anomaly, this paper uses data mining techniques to find the abnormal data in the stock market data, and uses the isolated point detection method based on density and distance to analyze the obtained abnormal data to obtain its implicit useful information. However, due to the defects of traditional data mining algorithms in dealing with stock market anomalies containing uncertain factors, that is, the errors caused by other human factors, this paper introduces the roughening entropy of the uncertainty data and applies its theory to the field of data mining, a data mining algorithm based on rough entropy in the US stock market anomaly is designed. Finally, the empirical analysis of the algorithm is carried out. The experimental results show that the data mining algorithm based on rough entropy proposed in this paper can effectively detect the abnormal fluctuation of time series in the stock market. Show more

Keywords: US stock market, data mining algorithm, outlier detection method, rough entropy

DOI: 10.3233/JIFS-189006

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5213-5221, 2020