Neural Network-based Forecasting Research Of Earthquake Disaster Loss

In our country is the higher frequency of earthquake, earthquake restricting economic construction, social development, a serious impact on the people’s work and life, endanger the personal safety of people. Also due to China for the lack of earthquake disaster insurance service, did not play on earthquake damage was the role of risk management. Thus for the prediction of earthquake disaster loss can not only make reference to earthquake disaster prediction research, at the same time, the development of China earthquake disaster insurance service also can be guidance.This paper has three parts, the first part introduces the earthquake disaster characteristics and earthquake disaster loss factors, the earthquake disaster prediction were classified; The second part mainly introduces the mathematical model of this paper: neural network model, including the type of model, algorithm and so on; the third part of this paper, the selection of 2013-2014 national seismic data as the research object, the data of collection and sorting, respectively, using the same static BP neural network model and radial basis function neural network model to study the earthquake disaster loss. The results of the study showed that RBF neural network model in the earthquake disaster loss prediction, The result is not only fast but also more accurate.