Short-term Power Load Forecasting based on Fuzzy-RBF Neutral Network

The paper proposes short-term power load forecasting model based on fizzy RBF neural network, it has overcome the BP algorithm's disadvantage of slow convergence rate and it fall into partially the smallest insiffficiency easily. RBF network model in the use of the latest neighborhood clustering algorithm, and the network structure and the parameters are double- adjusted and the training speed and forecast accuracy are improved. The examples also show that the model can improve forecast accuracy effectively, reducing the error of load forecasting, and the inherent detects of BP neural network have been avoid.