The typhoon disaster loss data from 1992 to 2011 in Hainan Province are used ior statistical analysis. The principal component analysis is used by statistical analysis. The five main factors of disasters and four disaster indicators factor are identified in typhoon disaster. With the advantages of fuzzy logic and neural network in T-S fuzzy neural network, a T-S fuzzy neural network model is designed and applied to the losses forecast for the typhoon disaster, and the law of the typhoon disaster hazard factor with disaster indicators factors is studied using Quantitative method. Adjust the parameters in this model, control the learning performance error value and the total error , the performance of the model can be optimized. The prediction model which had established is applied to "Nock-ten" Typhoon disaster loss forecast and the experimental results show that the model has a better ability to predict the typhoon disaster losses. The prediction model will be better value for disaster mitigation and prevention.%使用1992-2011年间海南省台风灾害数据,综合T-S模糊神经网络的模糊逻辑和神经网络学习优化的性能,设计了一种灾害损失预测模型并定量地表达了台风灾害损失致灾因子与灾情指标因子之间的规律.调节模型的参数cij、σij和pij(k),控制学习性能指标误差值Ep和总误差E来优化模型的性能.将模型应用于201108号台风“洛坦”灾害损失预测中,实验结果表明该模型具有较好的预测功能.
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