Application of Decision Tree on Short-Term Load Forecasting
Jingfei Yang · Central China Electric Power · 2009
This paper presents the decision tree method to forecast the electrical load with diverse samples.Entropy and information gain is calculated to get the best decision tree.Entropy is also used to disperse continuous data attributes and get the best splitting point.The paper describes the way of generating decision tree rules which is applied to short-term load forecasting.Calculation result by the method on a real power grid is highly precise,which proves the applicability of the presented method.