Wavelet Gradient Boosting Regression Method Study in Short-Term Load Forecasting

The authors proposed gradient boosting regression method based on wavelet transform considering the influence of weather factors and the characteristics of the load and meteorological data. The load and meteorological data were decomposed into several subsequences in different band by wavelet transform respectively. Forecasting the load subsequence by building different gradient boosting regression model, lastly, the final forecasting result is attained via adding all child-load-serials forecasting results. It has been showed by load data of a city in north China that the method achieved good prediction accuracy.