Application of the generalized regression neural network in short-term load forecasting

Abstract

The generalized regression neural network(GRNN) is proposed for the power load forecasting. GRNN has strong nolinear mapping ability and supple network topology, and also has altitudinal fault-tolerant ability and robustness. It can meet nonlinear recognition and process predition of the dynamic system, and has better adaptability to dynamic forecasting and prediction problem in mechanism. The effectiveness of the model and algorithm with the example of power load forecasting have been proved and approximation capability and learning speed of GRNN is better than BP neural network.