A Genetic-Algorithm Support Vector Machine and D-S Evidence Theory Based Fault Diagnostic Model for Transmission Line

2019 ◽  
Vol 34 (6) ◽  
pp. 4186-4194 ◽  
Author(s):  
Xiaomin Wu ◽  
Dianhong Wang ◽  
Weihua Cao ◽  
Min Ding
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Transmission Line ◽  
Evidence Theory ◽  
Support Vector ◽  
Diagnostic Model ◽  
Fault Diagnostic

Fault Diagnosis for Rolling Bearing Based on Genetic-SVM Classifier

2011 ◽  
Vol 199-200 ◽  
pp. 620-624 ◽  
Author(s):  
Yun Jie Xu
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Support Vector ◽  
Svm Classifier ◽  
Diagnostic Model ◽  
Roller Bearings ◽  
Study Support ◽  
Frequency Demodulation

Fault diagnosis of roller bearings is very complex, so it is difficult to use the mathematical model to describe their faults. Whose developmental changes have dual trends of increase and fluctuation. In this study, support vector machine trained by genetic algorithm based on high frequency demodulation analysis is proposed to fault diagnosis of ball bearing. Genetic algorithm is used to determine training parameters of support vector machine in this model, which can optimize the support vector machine (SVM) an intelligent diagnostic model. The performance of the GSVM system proposed in this study is evaluated by roller bearings in the wood-wool production device. The experimental results indicate that the proposed support vector machine trained by genetic algorithm has good diagnosis results in the application.

Fault Diagnosis for Diesel Engine Cylinder Head Based on Genetic-SVM Classifier

2014 ◽  
Vol 590 ◽  
pp. 390-393 ◽  
Author(s):  
Xue Liang Zhang ◽  
Yun Jie Xu
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Diesel Engine ◽  
Cylinder Head ◽  
Support Vector ◽  
Svm Classifier ◽  
Diagnostic Model ◽  
Engine Cylinder ◽  
Frequency Demodulation

Fault diagnosis of Diesel engine cylinder head is very complex, so it is difficult to use the mathematical model to describe their faults. In this study, support vector machine trained by genetic algorithm based on high frequency demodulation analysis is proposed to fault diagnosis of Diesel engine cylinder head. Genetic algorithm is used to determine training parameters of support vector machine in this model, which can optimize the support vector machine (SVM) an intelligent diagnostic model. The performance of the GSVM system proposed in this study is evaluated by Diesel engine cylinder head in the wood-wool production device. The application to fault diagnosis for diesel engine shows the effectiveness o f the method.

Mutation probability of cytochrome P450 based on a genetic algorithm and support vector machine

2011 ◽  
Vol 6 (11) ◽  
pp. 1367-1376 ◽  
Author(s):  
Yu Yao ◽  
Tao Zhang ◽  
Yi Xiong ◽  
Li Li ◽  
Juan Huo ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Cytochrome P450 ◽  
Support Vector ◽  
Mutation Probability
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