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- W2353241946 abstract "Support vector machine(SVM) is widely applied in fault diagnosis field because it has many virtues than the traditional methods.But the standard SVM consumes more system memory and training time.proximal support vector machines(PSVM) has the characters of faster training speed and less system memory needed,it is suitable for the fault diagnosis of large scale of samples.But the classification accuracy is not very good to the samples nearby the separating plane.In order to resolve this problem of PSVM,Vague-Sigmoid kernel function is utilized to improve the diagnosis accuracy of PSVM to the samples nearby the separating plane in this paper.The simulation is done to testify that this method is effective." @default.
- W2353241946 created "2016-06-24" @default.
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- W2353241946 date "2012-01-01" @default.
- W2353241946 modified "2023-09-26" @default.
- W2353241946 title "Fault diagnosis algorithm research of proximal support vector machine based on Vague-sigmoid kernel" @default.
- W2353241946 hasPublicationYear "2012" @default.
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