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Application of Brownian model in the north- western Beijing, China
引用本文:冉洪流,周本刚. Application of Brownian model in the north- western Beijing, China[J]. 地震学报(英文版), 2004, 17(Z1)
作者姓名:冉洪流  周本刚
作者单位:Institute of Geology,China Earthquake Administration,Beijing 100029,China,Institute of Geology,China Earthquake Administration,Beijing 100029,China
基金项目:地震科学联合基金,Key Project "Assessment of Seismic Safety" from China Earthquake Administration during the tenth Five-year Plan
摘    要:Introduction Since the tens years, the research on active fault has been stepped from qualitative phase toquantitative phase. With the developing of research on fault activity, fault segmentation, interac-tion among the adjacent or near fault segments, geodetic and paleoearthquake, scientists have re-alized that strong earthquake recurrence along active fault has different properties and multiplepatterns (Working Group on California Earthquake Probabilities, 1988, 1990, 1995, 1999, 2003…


Application of Brownian model in the northwestern Beijing, China
RAN Hong-liu ZHOU Ben-gang Institute of Geology,China Earthquake Administration,Beijing ,China. Application of Brownian model in the northwestern Beijing, China[J]. Acta Seismologica Sinica(English Edition), 2004, 17(Z1)
Authors:RAN Hong-liu ZHOU Ben-gang Institute of Geology  China Earthquake Administration  Beijing   China
Affiliation:Institute of Geology, China Earthquake Administration, Beijing 100029, China
Abstract:The mathematic theory of Brownian passage-time model and its difference from other recurrence models such asPoisson, lognormal, gamma and Weibull, were introduced. We assessed and analyzed the earthquake probabilitiesof the major faults with the elapsed time much greater than the recurrence interval in the northwest region of Beijing (China) in 100-year by using both Brownian passage-time model and Poisson model, and concluded that thecalculated results obtained from Brownian passage-time model is more reasonable.
Keywords:recurrence model  active fault  elapsed time  recurrence interval  conditional probability
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