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地震 ›› 2005, Vol. 25 ›› Issue (2): 19-25.

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径向基函数(RBF)神经网络及其应用

王炜1, 吴耿锋2, 张博锋2, 王媛2   

  1. 1.上海市地震局, 上海 200062;
    2.上海大学计算机学院, 上海 200072
  • 收稿日期:2004-07-05 修回日期:2004-09-22 出版日期:2005-04-30 发布日期:2021-11-10
  • 作者简介:王炜(1947-), 男, 江苏南京人, 研究员, 主要从事地震学、 地震预报等研究。
  • 基金资助:
    “十五”科技部科技攻关项目(2001BA601B01-04-04)

Neural networks of radial basis function (RBF) and it′s application to earthquake prediction

WANG Wei1, WU Geng-feng2, ZHANG Bo-feng2, WANG Yuan2   

  1. 1. Earthquake Administration of Shanghai Municipality, Shanghai 200062;
    2. Computer Institute of shanghai University, Shanghai 200072, China
  • Received:2004-07-05 Revised:2004-09-22 Online:2005-04-30 Published:2021-11-10

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摘要： 介绍了径向基函数(RBF)神经网络的原理、 学习算法及其在地震预报专家系统ESEP 3.0中的应用。 实际应用结果表明, 该神经网络可以很好地克服BP神经网络学习过程的收敛过分依赖于初值和可能出现局部收敛的缺陷, 具有较快的运算速度、 较强的非线性映射能力和较好的预报效能。

关键词: 径向基函数神经网络, BP神经网络, 学习方法, 专家系统

Abstract: the principle and algorithm of neural networks of Radial Basis Function (R BF) and its application to the expert system for earthquake prediction (ESEP 3.0) are introduced in this paper. The actual application in earthquake forecast shows that the neutral networks can overcome some demerit of BP neural networks in leaning process, the constringency excessively depend on initial value and optimization constringency and often can′t appear. The RBF neural networks possess the rapid operation speed in learning and strong nonlinear mapping ability and very good efficiency.

Key words: Neural networks of radial basis function, BP neural networks, Learning method, Expert system

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