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- W2358303986 abstract "Research the problem of transformer fault diagnosis.The latent faults in transformer can be found timely through the qualitative and quantitative analysis of the gas dissolved in transformer oil.But the problems of slow convergence speed and instability exist in the diagnosis method based on neural network at present,which leads to low accuracy rate.In order to solve the problems,an improved neural network model of niche genetic algorithm was presented.It makes good use of searching ability of niche genetic algorithm and the nonlinear reflection and association learning ability of the neural network,and optimizes the initial connection weights and thresholds of the neural network through the niche genetic algorithm,then trains and tests the network.The result of the experiment shows that,compared with the traditional method,the improved model is effective to improve convergence rate,stability of network and accuracy of fault diagnosis,and has very strong feasibility and validity." @default.
- W2358303986 created "2016-06-24" @default.
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- W2358303986 date "2012-01-01" @default.
- W2358303986 modified "2023-09-23" @default.
- W2358303986 title "Application of Improved Neural Network in Transformer Fault Diagnosis" @default.
- W2358303986 hasPublicationYear "2012" @default.
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