Wind speed forecasting is very important to the transaction planning and the operation reliability of power system in wind farm.According to the mechanism that the wind is formed, the influencing factor and its variation rule, a method of pattern recognition and adaptive neuron-fuzzy inference system for wind speed forecasting is presented in this paper. The hybrid algorithm is used to train the parameter of the fuzzy inference system. Inputted the related data to the trained model and anticipated wind speed is gotten. The Maui island of Hawaii is used as our case study, the predicted result shows applying this approach into practice would be valid.