Research Of Load Forecast Based On Fuzzy Theory And Artificial Neutral Networks

Traditional load forecast method had many deficiencies, such as poor precision and crudeness and incapability for non-linear relations. But Fuzzy theory and neural networks is good at dealing system problem caused by inaccuracy and non-linear relations. Neural networks is had to extract and express knowledge, the fuzzy method actually is good at processing undetermined problem by simulate person's experience processes;At the same time, fuzzy system is hard to get study rule from training sets, but neural network stronger study ability, it can reduce the fuzziness with association memory, thus fuzzy-neural network forecast method has been induced.This paper has adopts Particle Swarm Optimization Algorithm to train the neural networks, which is a kind of global optimization technology. It uses the interaction between particles to search solution space, and find the best one. The results show that the method can enhance the accuracy and efficiency of neural networks in load forecasting.