Application of GRNN Neural Network in Short Term Load Forecasting

According to the short-term power load has a strong feature of time series, based on the joint probability density theory, GRNN neural network model is introduced to solve the load forecasting problem. By comparison with actual examples and algorithm analysis of sensitivity, the method proposed in this thesis has high prediction accuracy and strong robustness.