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《Computer Engineering》 2005-04
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Application for Electricity Price Forecasting Using Improved Wavelet Neural Networks Based on GA

DONG Fugui1, ZHANG Shiying1, TAN Zhongfu2, ZHANG Wenquan2 (1. School of Management, Tianjin University, Tianjin 300072; 2. School of Business Management, North China Electric Power University,Beijing 102206)  
The accuracy of the electricity price forecasting is very important to power plants bidding decision. In order to avoid the limitation of the BP neural networks, this paper establishes the electricity price forecasting model using wavelet neural networks based on the genetic algorithm. The model combines the global optimization searching performance of the genetic algorithm and the time-frequency localization of the wavelet neural networks. The example shows that this model can effectively improve the forecasting precision and avoid the limitation of the BP neural networks model.
【Fund】: 国家自然科学基金资助项目(70373017)
【CateGory Index】: TP183
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