地震序列类型的确定与现场预报规则的获取  

Determination of sequence type and knowledge self-learning

作　　者：庄昆元[1] 王炜[1] 黄冰树[2] 章纯[1] 

机构地区：[1]上海市地震局,上海200062 [2]上海材料研究所,上海200437

出　　处：《地震》2001年第3期15-20,共6页Earthquake

基　　金：上海市科技发展基金项目 ( 94 2 912 10 )

摘　　要：论述了“震后趋势决策支持系统 PTDSS”中的知识学习问题。以某些地震参数与序列类型的关系为例 ,介绍了如何确定地震序列类型以及系统通过 FAM模型进行机器学习的方法。In this paper the problem of self learning in the Post earthquake Tendency Decision Support System (PTDSS) is discussed. The method of Fussy Associative Memory is introduced for solving this problem, and a digital method for determination of earthquake sequence type is presented. A great deal of meaningful experience are obtained in this system by self learning which can be used to determine the sequence type in early stage of sequence. The examples show that this digital method is more efficient for the classification of sequence type than the traditional one.

关 键 词：地震序列 地震类型 神经网络 模糊联想记忆FAM模型 震后趋势决策支持系统 地震现场预报 

分 类 号：P315.7[天文地球—地震学]