Medium and Long-Term Load Forecasting Based on PCA and BP Neural Network Method

To settle the problem which the precision and generalization performance of forecast model is affected easily by input variable, the method which reconstructs the original input space of back-propagation neural network by principal component analysis that can eliminate the relevance of value is researched. The method can not only reduce duplicated information but also extract the leading factors. Its can also optimize its network structure as well as enhance the network´s forecast precision. The effectiveness of the proposed algorithm is verified by the practical data.