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- W2359694025 abstract "A fault diagnosis method for oil-immersed transformer based on LS-SVM which is optimized by CSA is presented.This method takes five kinds of dissolved gas content as fault characteristics,and integrates fault samples with CSA algorithm and k-fold cross-validation to train and optimize the LS-SVM model based on one-against-one(1-a-1) classifying combination.The derived model is applied in fault diagnosis classification.Testing set show that the coding loss and too absolute coding boundary problems with the improved three ratio method can be avoided by the method,and the derived LS-SVM model gets more stable diagnostic effects than BP,RBF neural network while its accuracy is also higher than the LS-SVM with one-against-all(1-a-a) classifying combination.The proposed method has good practical value." @default.
- W2359694025 created "2016-06-24" @default.
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- W2359694025 date "2011-01-01" @default.
- W2359694025 modified "2023-09-26" @default.
- W2359694025 title "A fault diagnosis method for oil-immersed transformer based on LS-SVM optimized by CSA" @default.
- W2359694025 hasPublicationYear "2011" @default.
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