Support vector machine(SVM)was used to study the stability problem of high pressure unloading diaphragm pressure reducing regulator in the turbine gas seal pressure reducing test system.The research mainly focused on multi-structural parameters variation,which was difficult to solve by the classical methods.By comparing SVM and back propagation(BP)neural network model in the scarce and incomplete data set,several conclusions were proposed:the prediction models of SVM can get 25.5%less error in average and a...
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