Rainfall Forecasting using Neural Network with MATLAB
The continuously cloudy / rainy forecast is an important basis that is used to make choice of wheat harvest time but multiple regression weather forecast models hardly content the rate of required accuracy. MATLAB neural-network toolbox is composed of a series of typical neural network activation functions that make computing network output into calling activation functions. BP artificial neural network that is based on MATLAB platform and utilizes error back propagation algorithm to revise network weight has dynamic frame characteristics and is convenient for constructing network and programming. After it has been trained by input Rainfall samples, network forecast model that has three neural cells possesses very good generalization capability. After we contrast fitting rate and accuracy rate of network model with ones of regression model, network model has a distinct advantage over regression model.