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地震 ›› 2001, Vol. 21 ›› Issue (3): 15-20.

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地震序列类型的确定与现场预报规则的获取

庄昆元1, 王炜1, 黄冰树2, 章纯1   

  1. 1.上海市地震局,上海 200062;
    2.上海材料研究所,上海 200437
  • 收稿日期:2000-12-26 修回日期:2001-04-01 出版日期:2001-07-31 发布日期:2022-06-02
  • 作者简介:庄昆元(1935-),男,浙江镇海人,研究员,主要从事地震预报研究。
  • 基金资助:
    上海市科技发展基金项目(94291210)

Determination of sequence type and knowledge self-learning

ZHUANG Kun-yuan1, WANG Wei1, HUANG Bing-shu2, ZNANG Chun1   

  1. 1. Seismological Bureau of Shanghai Municipality, Shanghai 200062, China;
    2. Material Institute of Shanghai Municipality, Shanghai 200437, China
  • Received:2000-12-26 Revised:2001-04-01 Online:2001-07-31 Published:2022-06-02

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。通过学习系统得到了一批非常有用的早期判断序列类型的知识。

关键词: 地震序列, 地震类型, 机器学习, 神经网络, 模糊联想记忆FAM模型

Abstract: 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.

Key words: Earthquake sequence, Earthquake type, Machine learning, Neural network, Fussy associative memory FAM model

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