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Computer Engineering

China Simulation Federation

Journal

2021

Support vector machine

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Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan Nov 2021

Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan

Journal of System Simulation

Abstract: In view of the complexity and low accuracy of gait recognition in the past, an intelligent gait recognition method based on plantar pressure perception is proposed. The pressure data of the gait of plantar periodic motion is collected and the obtained gait data is classified by the vector machines,the intelligent gait recognition of plantar pressure perception is realized, and the accuracy of gait feature analysis is improved. Through experiment verification, the overall classification accuracy of the classifier is more than 90%, which verifies the rationality of the feature extraction. By evaluating the real state and the results of …


Fault Diagnosis Of Mechanical Equipment Based On Ga-Svr With Missing Data In Small Samples, Jingjing Wei, Qinming Liu, Chunming Ye, Guanlin Li Jun 2021

Fault Diagnosis Of Mechanical Equipment Based On Ga-Svr With Missing Data In Small Samples, Jingjing Wei, Qinming Liu, Chunming Ye, Guanlin Li

Journal of System Simulation

Abstract: In view of the equipment fault diagnosis with small and missing sample data, a method of missing data filling based on support vector regression optimized by genetic algorithm is proposed to improve the accuracy of equipment fault diagnosis. The support vector regression optimized by genetic algorithm was trained by other data values of missing data, and univariate prediction results were obtained. The training set was reconstructed through correlation analysis, so as to obtain the multivariate prediction results. Dynamic weights were established to combine univariate prediction results and multivariate prediction results to fill in the missing data. The …


Safety Evaluation And Risk Level Prediction Of Driving Behavior Considering Multi-Factors Influence, An Yu, Pengpeng Jiao, Zixiu Bai Jan 2021

Safety Evaluation And Risk Level Prediction Of Driving Behavior Considering Multi-Factors Influence, An Yu, Pengpeng Jiao, Zixiu Bai

Journal of System Simulation

Abstract: In order to study the influence of multi-factors of human-vehicle-road on driving behavior and vehicle safety status in road traffic system, a simulated driving comparison test of six scenarios combined by multiple factors is designed. Driving simulator, physiography and eye tracker are used to collect 19 indicators related to driving behavior respectively. The differences of sample data are compared by variance analysis. The nonlinear SVM(support vector machine) is used to classify and predict the sample data. The driving behavior risk level prediction model is established, and the validity of the model is verified by the experimental data. The …