Short-term load forecasting based on bayes and RS

Abstract

In the many influencing factors of load forecasting, some are related to each other, and some are independent, so it is not very necessary of all factors to the conclusions. The paper adaptively selects input features making use of Bayes method and Rough Set, and chose a group of input characteristic set which report most out the reason of output change to train the BP Neural Network model for forecasting, which has been testified to be valid. © 2010 Springer-Verlag Berlin Heidelberg.