THE RAINFALL FORECAST MODEL OF PCA-RBF NEURAL NETWORKS BASED ON MATLAB
Jifu Nong · Journal of Tropical Meteorology · 2008
Based on previous 500 hPa geopotential height and sea surface temperatures,a prediction model of the monthly mean rainfall in May for the central part of Guangxi is established with RBF neural network technology and principal component analysis(PCA) method.The results of the forecast experiment with 5-year samples indicate that the mean relative error is 18.12%,the root mean square error is 50.52,and the mean absolute error is 34.23.The prediction results of RBF neural network are proved to be more accurate compared with BP neural network model.