冯德益1, 楼世博2, 顾瑾平1, 钟廷姣1, 林命週3, 陈化成2. 1984: 模糊数学方法在地震综合预报中的应用. 地震学报, 6(2): 146-158.
引用本文: 冯德益1, 楼世博2, 顾瑾平1, 钟廷姣1, 林命週3, 陈化成2. 1984: 模糊数学方法在地震综合预报中的应用. 地震学报, 6(2): 146-158.
PENG DEYIup, LOU SHIBOup2, GU JINPINGup, ZHONG TINGJIAOup, LIN MINGZHOUup3, CHEN HUACHENGup2aaota href=hass=. 1984: THE APPLICATION OF FUZZY MATHEMATICS IN MULTI-APPROACH EARTHQUAKE PREDICTION. Acta Seismologica Sinica, 6(2): 146-158.
Citation: PENG DEYIup, LOU SHIBOup2, GU JINPINGup, ZHONG TINGJIAOup, LIN MINGZHOUup3, CHEN HUACHENGup2aaota href=hass=. 1984: THE APPLICATION OF FUZZY MATHEMATICS IN MULTI-APPROACH EARTHQUAKE PREDICTION. Acta Seismologica Sinica, 6(2): 146-158.

模糊数学方法在地震综合预报中的应用

THE APPLICATION OF FUZZY MATHEMATICS IN MULTI-APPROACH EARTHQUAKE PREDICTION

  • 摘要: 本文的目的,是把模糊数学中发展起来的模糊识别的直接方法与间接方法,试用于地震综合预报.模糊识别的直接方法,就是直接由前兆指标的从属函数来估计地震危险性并进行预报,其效果依赖于建立前兆指标的从属函数的技巧.文中以地下水氡含量、视电阻率、波速等前兆资料为基础,提出了一种主要依据前兆变化速率及相关系数,并使用其它途径来建立从属函数的具体方法与公式.使用这样的从属函数之后,可以更好地识别出前兆异常,并且更容易区分出异常的起始、终结或发生明显转折的时期.模糊识别的间接方法,本文中采用的是模糊聚类分析方法,它与选取表示型类区别的相似系数或距离有关.我们这里采用的是基于模糊等价关系的聚类分析方法.此方法包括以下步骤:将一系列样本按彼此间的相似程度建立一个模糊相容关系;通过合成运算把这个模糊相容关系改造为一个模糊等价关系;选择一个适当的参数的数值,并对原始样本进行分类.选取某一给定地区的地震活动性的一些统计指标,或者选取由多手段单台或单手段多台得出的一些前兆数据(地形变、地下水氡含量、视电阻率等等),就可以使用上述模糊聚类分析方法来进行地震综合预报.作为说明此方法的例子,文中给出了对我国西部强震及中强震得出的一些初步结果.由所得结果可以看出,利用模

     

    Abstract: In this paper, the direct and indirect methods for fuzzy recognition developed in fuzzy mathematics are applied to the study of multi-approach earthquake prediction.The direct method for fuzzy recognition consists of assessment of earthquake risk and making prediction by use of membership functions of different precursors directly. Its effectiveness depends on the technique of constructing these membership functions. Based on the various data of radon content of underground water, apparent earth resistivity, seismic velocities and other precursors, the concrete methods and formulae for constructing the corresponding membership functions have been suggested by employing mainly the rate of precursor change and coefficient of correlation and by other means. In applying these menbership functions, the abnormal features of a precursor can be recognized more clearly and the times of beginning, finishing or transitions of an anomaly more easily.The indirect method for fuzzy recognition, used in this paper, is the method of fuzzy clustering analysis, which depends on the selection of similarity coefficient or distance. Here we use a method of clustering analysis based on the fuzzy equivalent relation. This method includes the following steps: obtaining first a fuzzy compatible relation according to the degrees of similarities between samples; then transforming this compatible relation into a fuzzy equivalent relation by use of combinational operation; finally selecting a suitable value for parameter A, and classifying the original samples.Taking some statistical indices of seismicity in a given region, or taking the data of a number of precursors observed (crustal deformation, radon content of underground water, apparent resistivity etc.) at one station or of one precursor at a series of stations, then multi-approach earthquake prediction may be made by using the method of fuzzy clustering analysis as mentioned. For illustration of this method some preliminary results obtained for large and moderate earthquakes occurred in the western part of China were shown. It can be seen from these results that the prediction by using fuzzy clustering analysis is generally in better conformity with the actual cases of earthquake occurrence.It is considered therefore that the prospect for using the methods of fuzzy mathematics in multi-approach earthquake prediction is optimistic.

     

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