混合二维泊松过程的分解算法及其在提取地震丛集模式中的应用
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摘要
将一定范围内的地震数据假设为背景地震和丛集地震的叠加 ,并同时认为背景地震和丛集地震分别满足不同参数的二维泊松过程 .通过引入N阶距离概念 ,将叠加的二维泊松过程转化为一维的混合密度函数 ,在对距离阶数进行选择的基础上 ,最终采用遗传算法进行混合密度分解 ,以达到提取地震丛集模式的效果 .文中将该算法应用于我国西南地区松潘及龙陵主震前丛集地震的提取 ,并与C值的时间扫描结合 ,深化了这两次大地震前地震活动图象的认识
Aiming at the complexity of seismic gestation mechanism and spatial distribution , we hypothesize that the seismic data are composed of background earthquakes an d anomaly earthquakes in a certain temporal-spatial scope. Also the background earthquakes and anomaly earthquakes both satisfy the 2-D Poisson process of dif ferent parameters respectively. In the paper, the concept of N-th order dis tance is introduced in order to transform 2-D superimposed Poisson process into 1-D mixture density function. On the basis of choosing the distance, mixture d ensity function is decomposed to recognize the anomaly earthquakes through genet ic algorithm. Combined with the temporal scanning of C value, the algorithm is applied to the recognition on spatial pattern of fore shock anomalies by exam ples of Songpan and Longling sequences in the southwest of China.
Aiming at the complexity of seismic gestation mechanism and spatial distribution , we hypothesize that the seismic data are composed of background earthquakes an d anomaly earthquakes in a certain temporal-spatial scope. Also the background earthquakes and anomaly earthquakes both satisfy the 2-D Poisson process of dif ferent parameters respectively. In the paper, the concept of N-th order dis tance is introduced in order to transform 2-D superimposed Poisson process into 1-D mixture density function. On the basis of choosing the distance, mixture d ensity function is decomposed to recognize the anomaly earthquakes through genet ic algorithm. Combined with the temporal scanning of C value, the algorithm is applied to the recognition on spatial pattern of fore shock anomalies by exam ples of Songpan and Longling sequences in the southwest of China.
引文
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邓永录,梁之舜.1998.随机点过程及其应用[M ].北京:科学出版社,1～16
刁守中,郭爱香,王红卫.1994.华北地区早期背景地震活动特征与M≥7大震危险区预测[J].高原地震,6(2):40～46
国家地震局分析预报中心编.1989.中国西部地震目录(1976—1979,M≥1)[M ].北京:地震出版社,1～321
焦远碧,吴开统,杨满栋.1990.我国地震台网检测能力及台网观测条件质量评定[J].中国地震,6(4):1～7
梅世蓉,冯德益,张国民.1993.中国地震预报概论[M].北京:地震出版社,493～495
王炜,潘坚云,黄冰树.1989.地震空间集中度C值及其在地震预报中的应用[A].见:国家地震局科技司编.地震预报方法实用化研究文集(地震学专集)[C].北京:学术期刊出版社,127～141
王炜,戴维乐,宋俊高.1999.地震空间集中度C值在华北中强以上地震前的中期异常变化[J].地震研究,22(1):51～56
周成虎,骆剑承,杨晓梅,等.1999.遥感影像地学理解与分析[M].北京:科学出版社,185～255
周明,孙树栋.1999.遗传算法原理及应用[M].北京:国防工业出版社,1～77
中国地震局预测预报司编.1998.大陆地震预报的方法和理论中国“八五”地震预报研究进展[M ].北京:地震出版社,1～523
BethouxN ,OuillonG ,NicolasM .1998.TheinstrumentalseismicityofthewesternAlps:Spatio temporalpatternanalysedwiththewavelettransform[J].GeophysJInt,135:177～194
CeleuxG ,GovaertG .1992.AclassificationEMalgorithmandtwostochasticversions[J].ComputationalStatisticsandDataAnalysis,14:315～332
DasguptaA ,RafteryAE .1998.Detectingfeaturesinspatialpointprocesseswithclutterviamodel basedclustering[J].JAmerStatisticalAssoc,93:294～302
DaveR .1992.Characterizationanddetectionofnoiseinclustering[J].PatternRecognitionLetters,12:657～664
FraleyC ,RafteryAE .1998.Howmanycluster?Whichclusteringmethod?—Answerviamodel basedclusteranalysis[J].ComputerJ,41:578～588
KrzysztofJC ,WitoldP ,RomanWS .1998.Dataminingmethodforknowledgediscovery[M ].Norwell:KluwerAcademicPublishers,1～97
LeeWHK ,BrillingerDR .1979.OnChineseearthquakehistory—anattempttomodelanincompletedatasetbypointprocessanalysis[J].PureApplGeophys,117:1229～1257
ToddKM .1996.Theexpectation maximizationalgorithm[J].IEEESignalProcessingMagazine,11:47～60
WyssM ,ToyaY .2000.IsbackgroundseismicityproducedatastationaryPoissonianrate[J].BullSeismSocAmer,90(5):1174～1187
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