【摘要】 基于贝叶斯原理,建立了地震事件识别判据的综合方法(简称贝叶斯方法),并针对中亚地区大量地震事件,采用该方法综合了不同台站和不同频带的P/S震相幅值比判据.该方法的主要优点是能够给出事件属于爆炸的概率,而且充分考虑了判据之间的相关性.理论计算和模拟数据分析结果表明,贝叶斯方法是最优的综合方法,其识别效果比任何单个判据好,也好于普通线性组合方法的识别效果.针对中亚地区大量地震事件综合不同台站和不同频带的P/S震相幅值比判据的结果也表明,贝叶斯方法的误识率低于单个判据和线性组合方法的误识率.更多还原

【Abstract】 A multivariate discrimination technique was established based on the Bayesian theory.Using this technique,P/S ratios of different types(e.g.,Pn/Sn,Pn/Lg,Pg/Sn or Pg/Lg)measured within different frequency bands and from different stations were combined together to discriminate seismic events in central Asia.Major advantages of the Bayesian approach are that the probability to be an explosion for any unknown event can be directly calculated given the measurements of a group of discriminants,and at the same time correlations among these discriminants can be fully taken into account.It was proved theoretically that the Bayesian technique would be optimal and its discriminating performance would be better than that of any individual discriminant as well as better than that yielded by the linear combination approach ignoring correlations among discriminants.This conclusion was also validated in this paper by applying the Bayesian approach to the above-mentioned observed data.更多还原