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The medium- and short-term prediction methods of strong earthquakes based on neural network
作者姓名:韩志强  王碧泉
作者单位:ZHI QIANG HAN BI QUAN WANGInstitute of Geophysics,State Seismological Bureau,Beijing 100081,China
摘    要:Themedium┐andshort┐termpredictionmethodsofstrongearthquakesbasedonneu┐ralnetworkZHI-QIANGHAN(韩志强)BI-QUANWANG(王碧泉)Instituteof...

收稿时间:18 March 1996
修稿时间:15 May 1996

The medium and short term prediction methods of strong earthquakes based on neural network
ZHI QIANG HAN BI QUAN WANGInstitute of Geophysics,State Seismological Bureau,Beijing ,China.The medium- and short-term prediction methods of strong earthquakes based on neural network[J].Acta Seismologica Sinica(English Edition),1997,10(4):459-467.
Authors:ZHI QIANG HAN BI QUAN WANGInstitute of Geophysics  State Seismological Bureau  Beijing  China
Institution:(1) Institute of Geophysics, State Seismological Bureau, 100081 Beijing, China
Abstract:The field of neural network has found solid application in the past ten years and the field itself is still developing rapidly. Neural network is composed of many simple elements operating in parallel. A neural network can be trained to perform a particular mapping and this is the basis of its application to practical problems. In this paper, new methods for predicting the strong earthquakes are presented based on neural network. Neural network learns from existing earthquake sequences or earthquake precursors how to make medium and short term prediction of strong earthquakes. This paper describes two neural network prediction models. One is the model based on earthquake evolution sequences, which is applied to the modeling of the magnitude evolution sequences in the Mainland of China, the other is based on earthquake precursors, which is applied to the modeling of the occurrence time of strong earthquakes in North China. Test results show that the prediction methods based on neural networks are efficient, and convenient. They would find more application in the future.
Keywords:earthquake prediction  neural network  modeling  earthquake evolution sequence  earthquake precursor
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