| The inversion of anelastic coefficient,source parameters and site respond using genetic algorithm |
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| 作者姓名： | 刘杰 郑斯华 黄玉龙 |
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| 作者单位： | [1]CenterforAnalysisandPrediction,ChinaSeismologicalBureau,Beijing100036,China [2]DepartmentofCivilandStructuralEngineering,HongKongPolytechnicUniversity,HongKong,China |
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| 摘 要： | It gradually becomes a common work using large seismic wave data to obtain source parameters, such as seismic moment, break radius, stress drop, with completingof digital seismic network in China (Hough, et al, 1999; Bindi, et al, 2001). These parameters are useful on earthquake prediction and seismic hazard analysis.Although the computation methods of source parameters are simple in principle and the many research works have been done, it is not easy to obtain the parameters accurately. There are two factors affecting the stability of computation results. The first one is the effect of spread path and site respond on signal. According to the research results, there are different geometrical spreading coefficients on different epicenter distance. The better method is to introduce trilinear geometrical spreading model (Atkinson, Mereu, 1992; Atkinson, Boore, 1995; WONG, et al, 2002). In addition, traditional site respond is estimated by comparing with rock station, such as linear inversion method (Andrews, 1982), but the comparative estimation will introduce some errors when selecting different stations. Some recent research results show that site respond is not flat for rock station (Moya, et al, 2000; ZHANG,. et al, 2001; JIN, et al, 2000; Dutta, et al, 2001). The second factor is to obtain low-frequency level and corner frequency fromdisplacement spectrum. Because the source spectrum model is nonlinear function,these values are obtained by eye. The subjectivity is strong. The small change of corner frequency will affect significantly the result of stress drop.
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| 关 键 词： | 遗传算法 弹性系数 地震波 地应力 数字地震台网 震源参数 |
| 收稿时间： | 9 May 2002 |
| 修稿时间： | 9 December 2002 |
The inversion of anelastic coefficient, source parameters and site respond using genetic algorithm |
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| Liu Jie , Zheng Si-hua and Wong Yuk-Lung.The inversion of anelastic coefficient,source parameters and site respond using genetic algorithm[J].Acta Seismologica Sinica(English Edition),2003,16(2):226-232. |
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| Authors: | Liu Jie Zheng Si-hua and Wong Yuk-Lung |
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| Institution: | 1. Center for Analysis and Prediction, China Seismological Bureau, Beijing 100036, China
2. Department of Civil and Structural Engineering, Hong Kong Polytechnic University, Hong Kong, China |
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| Abstract: | It gradually becomes a common work using large seismic wave data to obtain source parameters, such as seismic moment, break radius, stress drop, with completingof digital seismic network in China (Hough, et al, 1999; Bindi, et al, 2001). These parameters are useful on earthquake prediction and seismic hazard analysis.Although the computation methods of source parameters are simple in principle and the many research works have been done, it is not easy to obtain the parameters accurately. There are two factors affecting the stability of computation results. The first one is the effect of spread path and site respond on signal. According to the research results, there are different geometrical spreading coefficients on different epicenter distance. The better method is to introduce trilinear geometrical spreading model (Atkinson, Mereu, 1992; Atkinson, Boore, 1995; WONG, et al, 2002). In addition, traditional site respond is estimated by comparing with rock station, such as linear inversion method (Andrews, 1982), but the comparative estimation will introduce some errors when selecting different stations. Some recent research results show that site respond is not flat for rock station (Moya, et al, 2000; ZHANG,. et al, 2001; JIN, et al, 2000; Dutta, et al, 2001). The second factor is to obtain low-frequency level and corner frequency fromdisplacement spectrum. Because the source spectrum model is nonlinear function,these values are obtained by eye. The subjectivity is strong. The small change of corner frequency will affect significantly the result of stress drop. |
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| Keywords: | source parameter site respond quality factor genetic algorithm |
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