Comparison of Two Methods Basing on Artificial Neural Network and SVM in Fault Diagnosis
Автор: Chunming Li, Huiling Li
Журнал: International Journal of Information Engineering and Electronic Business(IJIEEB) @ijieeb
Статья в выпуске: 1 vol.2, 2010 года.
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Two diagnosis methods based on a neural network classifier and SVM are proposed for a pulse width modulation voltage source inverter. They are used to detect and identify the transistor open-circuit fault. BP neural network (BPNN) is capable of recognition. However, it has shortcomings obviously. These are just advantages of SVM, which has ability of global search. As an alternative to ANN, SVM can offer higher detection efficiency and reliability.
Neural network, SVM, fault diagnosis
Короткий адрес: https://sciup.org/15013044
IDR: 15013044
Список литературы Comparison of Two Methods Basing on Artificial Neural Network and SVM in Fault Diagnosis
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