The Improved Load Forecasting Model of BP Neural Network
The traditional BP Neural Network forecasting model influenced clearly by the complexity of network frame and sample,which lead to the over-learning or low-extensive ability.The paper puts forward a new model to improve the BP Neural Network load forecasting model,which use attribution reduction algorithm of rough sets to reduce the various historical data related to the load and eliminate the property not related to the decision-making information.It was tested that this method reduces the input variables of the BP Neural Network,so shortens the training time of the BP Neural Network load forecasting model.At last the forecasting capability is improved.
BP Neural Network Load Forecasting Model Rough sets Attribution Reduction
Yanmei Li
School of Business and Administration,North China Electric Power University,Baoding,Hebei 071003,China
国际会议
大连
英文
628-633
2008-07-27(万方平台首次上网日期,不代表论文的发表时间)