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- W2393530275 abstract "Support vector machinerk will be able to adopt in the fault diagnosis of high voltage electric power metering system according to the advantage of the great adaptivity. Information in eight operation parameters of metering system will be extracted to be taken as the input values of the neural network, and a 4-bit binary number will be adopted to represent the normal circumstance and nine main fault types.Then the collected samples are used to train Elman network and 4 fault types will be selected to test the network. The results show that the Elman network model can effectively diagnose the fault of high voltage electric power metering system." @default.
- W2393530275 created "2016-06-24" @default.
- W2393530275 creator A5012302043 @default.
- W2393530275 date "2014-01-01" @default.
- W2393530275 modified "2023-09-25" @default.
- W2393530275 title "Application of Support Vector Machine in the Fault Diagnosis of High Voltage Electric Power Metering System" @default.
- W2393530275 hasPublicationYear "2014" @default.
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