人工神经网络在地震前兆混沌时间序列预测和处理中的应用

人工神经网络是用来模拟人脑智能特点和结构的一种模型，具有很强的非线性映射功能．把它引用到地震前兆观测数据的分析处理中，可为前兆观测更好地服务于地震分析预报开辟出一条新路，也是对人工神经网络方法应用的推广．本文分析了时间序列的可预测性，给出了用人工神经网络预测地震前兆混沌时间序列的方法，并以江宁台和徐州台SQ 型地倾斜仪观测及溧阳台体应变观测的时间序列为例，对其作了预测和处理．结果表明:用该方法处理达到的精度能满足实际工作的需要，因而该方法在今后的实际地震分析预报工作中具有重要应用价值． 

THE APPLICATION OF NEURAL NETWORK TO THE ANALYSIS OF EARTHQUAKE PRECURSOR CHAOTIC TIME SERIES

WT5BZ]Artificial neural network is such a model as to imitate the structure and intelligence feature of human brain, and of strong nonlinear mapping function. It is not only an extension of the application of artificial neural network model but also a new try for precursor observation to serve the earthquake prediction better that we use it in the analysis of earthquake precursor observation data. In this paper, we analyzed the predictability of time series and gave a method of application of artificial neural network in forecasting earthquake precursor chaotic time series. Besides, taking the ground tilt observation of Jiangning and Xuzhou Stations, the bulk strain observation of Liyang station for examples, we analyzed and forecasted their time series respectively. It is indicated that the precision of this method can meet the needs of practical task and therefore of great value in the application to the future practical earthquake analysis and prediction.