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- W2363188367 abstract "A wavelet decomposition based new approach to short-time load forecasting by artificial neural network (ANN) based on wavelet decomposition is proposed. Through the wavelet transform the load sequence is decomposed into subsequences on different scales, then using appropriate artificial neural networks these sub-sequences are forecasted by appropriate artificial neural networks respectively, finally after the synthesis of the forecasted results from the sub-sequences the final forecasting result of the load sequence is obtained. In the proposed method the wavelet decomposition can extract some periodical and nonlinear features of the load and subdivide them further, thus corresponding forecasting method can be used according to the coexisting rules of the subsequences themselves respectively; and the ANN possesses superiority in the processing of the problems which is nonlinear or its rule cannot be determinately displayed. The calculation results of a practical example show that the proposed method possesses high forecasting accuracy and better adaptability than traditional forecasting methods." @default.
- W2363188367 created "2016-06-24" @default.
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- W2363188367 date "2004-01-01" @default.
- W2363188367 modified "2023-09-23" @default.
- W2363188367 title "AN APPROACH TO SHORT-TERM LOAD FORECASTING BASED ON WAVELET TRANSFORM AND ARITFICIAL NEURAL NETWORK" @default.
- W2363188367 hasPublicationYear "2004" @default.
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