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- W4226488161 abstract "In order to exploit the data value of cyber-physical system and improve the risk prevention and control ability of distribution network, a fault prediction method for complex distribution network based on data association characteristics is proposed. Through data preprocessing, the fault level is divided, and the relevant meteorological characteristics of distribution network fault are summarized. The feature weight is calculated and sorted by random forest algorithm, and the optimal fault feature set is obtained. Then the fault level is predicted based on multi classification support vector machine algorithm. Through the analysis of practical examples, the proposed method can achieve high prediction effect, and the prediction results can provide an effective basis for distribution network risk pre control, which has practical application value." @default.
- W4226488161 created "2022-05-05" @default.
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- W4226488161 date "2021-12-23" @default.
- W4226488161 modified "2023-10-16" @default.
- W4226488161 title "Fault Prediction Method for Complex Distribution Network Based on Data Association Characteristics" @default.
- W4226488161 doi "https://doi.org/10.1109/ispec53008.2021.9735946" @default.
- W4226488161 hasPublicationYear "2021" @default.
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