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人工神经网络在徐州岩溶地面塌陷评价中的应用
引用本文:闫士民,闫长虹,刘健. 人工神经网络在徐州岩溶地面塌陷评价中的应用[J]. 江苏地质, 2007, 31(1): 45-49
作者姓名:闫士民  闫长虹  刘健
作者单位:南京大学地球科学系,南京大学地球科学系,江苏省地质调查研究院 江苏南京210093,江苏省第二地质工程勘察院,江苏徐州221004,江苏南京210093,江苏南京210018
摘    要:
岩溶地面塌陷的影响因素很多,发展过程也复杂。在众多的对岩溶地面塌陷的评价方法中,神经网络具有自学习、自适应与高度非线性映射的特点,是一种非常有效的评价手段。在徐州岩溶石地面塌陷的评价中,成功地运用了人工神经网络技术,它具有的强大非线性映射能力,能够建立评价因子和评价对象之间的关系,正确选取评价因子,避免主观判断取值,从而得出可靠的预测模型和岩溶塌陷危险性分区图。

关 键 词:岩溶地面塌陷  人工神经网络  工程地质  江苏徐州
文章编号:1003-6474(2007)01-0045-05
收稿时间:2005-12-16
修稿时间:2006-02-15

Application of artificial neural network on evaluation of karst ground subsidence in Xuzhou
YAN Shi-min,YAN Chang-hong,LIU Jian. Application of artificial neural network on evaluation of karst ground subsidence in Xuzhou[J]. Jiangsu Geology, 2007, 31(1): 45-49
Authors:YAN Shi-min  YAN Chang-hong  LIU Jian
Affiliation:1. Department of Earth Sciences, Nanjing University, Nanjing 210093, China; 2, No. 2 Geological and Engineering Exploration Institute of Jiangsu Province, Xuzhou 221004, Jiangsu ; 3.Geological Survey of Jiangsu Province, Nanjing 210018, China
Abstract:
There are many influence factors and complex evolvement course for karst ground subsidence.As a method with self-adaptive,self-study and nonlinear projected characters,the artificial neural network is effective among the evaluation methods.The evaluation of karst ground subsidence in Xuzhou shows that the relationship between factors and object of appraisement can be established and subjective judgement can be avoided by artificial neural network.Through establishment of a stable analysis model of artificial neural network and selection of evaluation factors,the perilous regional map of karst ground subsidence in Xuzhou City is obtained on the basis of engineering geological investigation and analysis of formation mechanism.
Keywords:Karst ground subsidence  Artificial neural network  Engineering geology  Xuzhou  Jiangsu
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