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- W4285190635 abstract "In this paper, the fault state of the outage line is judged based on the effective value of the single terminal voltage in the hot standby state of the outage line in the same tower and plays a guiding role in closing operation and troubleshooting of outage line in dispatching work. It has higher practical significance. This method inputs the single terminal voltage measurement value of outage line into radial basis kernel function support vector machine (RBF-SVM) and BP neural network to judge the fault state and fault type on outage line respectively. In order to verify the recognition accuracy of the proposed scheme, four different 500 kV double-circuit transmission line models with the same tower are established, and then simulated under different fault states. The results show that the accuracy of this method is 100% for the fault judgment on the hot standby line, and 99.4% for each fault type." @default.
- W4285190635 created "2022-07-14" @default.
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- W4285190635 date "2022-01-01" @default.
- W4285190635 modified "2023-09-23" @default.
- W4285190635 title "Fault Classification of Outage Transmission Lines Based on RBF-SVM and BP Neural Networks" @default.
- W4285190635 cites W2883916659 @default.
- W4285190635 doi "https://doi.org/10.1007/978-981-16-8052-6_101" @default.
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