Application for Short-Term Power Load Forecasting Using Improved Wavelet Neural Networks Based on GA

This paper optimizes the wavelet neural networks with genetic algorithms which has the optimization of the overall search capabilities, and establishes the model of wavelet neural networks based on genetic algorithms. It overcomes the shortcomings of BP neural network for their own, and it can get higher accuracy and faster convergence. The examples also show that the model can improve forecast accuracy effectively, reducing the error of load forecasting, and the inherent defects of BP neural network have been avoid.