As a neural network based on MSSE,ANN-MSE is not an appropriate solution to the problem of predicting rare weather event.In this paper,an improved neural network method,ANN-CE is presented,which is a three layered back-propagation neural network with one output unit.The error function of ANN-CE is a cross entropy function.Then utilizing ECMWF forecast fields data,this method was applied to 96 hours forecast of heavy precipitation event in northern Fijian province.The ANN-CE model and the ANN-MSE model based on original factor and principle component after PCA reducing dimensions were respectively built.These models were applied to independent samples in 2009-2010,and the test results are as following:TS grade for model based on principal component is higher than that of model based on original factors;miss-rate for the ANN-CE model is lower than that of the ANN-MSE model.All in all,ANN-CE model based on principal component has best performance and stability,whose TS grade and miss-rate was respectively 0.51 and 0.17,so it was suited for forecasting rare event.