| 模糊数学在地震活动性图象研究中的应用 |
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| 引用本文： | 冯德益,林命週,蒋淳,吴国有. 模糊数学在地震活动性图象研究中的应用[J]. 地震学报, 1987, 9(1): 15-27 |
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| 作者姓名： | 冯德益 林命週 蒋淳 吴国有 |
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| 作者单位： | 1. 天津市地震局2. 上海市地震局 |
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| 基金项目： | 国家地震局地震科学基金 |
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| 摘 要： | 本文应用模糊数学方法从给定地区的地震目录中识别出地震簇.这些地震簇由一系列时空相关的地震组成,每一次强震前都可能有其地震簇出现.两次地震的函数由以下公式来确定:eij=1e-1t+2e-2s计算出某一地区所有 MM0地震相互之间的联系强度,并取一个经验参数之后,就可以根据编网原则识别出地震簇.利用地震簇,可以把强震的地震活动性图象识别得更清楚,简单和定量化.此方法曾用于我国大华北及西南地区的地震簇识别与地震活动图象研究.清楚地识别出了13次大震(M6.5)的地震簇.研究了它们的时空特性.近似建立了 lg△t,lgL,lgS 与震级 M 间的线性经验关系,此处△t,L,S 分别表示地震簇的前兆时间(持续时间)及其震中分布的最大线度与面积.显然,这些关系式对地震预报研究可能有一定用途.
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APPLICATION OF FUZZY MATHEMATICS IN THE RESEARCH OF SEISMICITY PATTERN |
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| Affiliation: | 1. Seismological Bureau of Tianjin;2. Setsmologtcal Bureau of Shanghai |
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| Abstract: | A method of fuzzy mathematics has been applied to the recognition of seismic clusters from earthquake catalogues in a given region. A seismic cluster consists of a series of earthquakes related to each other in time and space. Every strong earthquake may be preceded by its seismic cluster. The fuzzy relative degree between two earthquakes has been determined as a function of time interval△t and distance △s by the formula:eij=1e-1t+2e-2s After calculating the degrees of relatedness of all earthquakes with MM0 in some region and taking an empirical parameter A, the seismic clusters can be recognized according to the principle of fuzzy netting.By use of seismic clusters the seismicity patterns of strong earthquakes can be recognized and studied more clearly, simply and quantitatively.This method have been applied to the recognition of seismic clusters and the study of seismicity pattern of earthquakes in North China and Southwest China. The seismic clusters of 13 large earthquakes (M6.5) have been recognized clearly, and their temporal and spatial distributions studied. The linear empirical relationships between lg△T, lgL, lgS and earthquake magnitude M have been constructed approximately, where △T, L and S are the premonitory time (duration), maximum linear dimension and the area of epicenter distribution of the seismic cluster respectively. Obviously, these relationships may be useful to earthquake prediction researches. |
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