[1]朱锦旗,焦珣,于军,等.基于GA-ANN的苏锡常地裂缝危险性评价[J].水文地质工程地质,2008,35(4):106-110.
 ZHU Jin-qi,JIAO Xun,YU Jun,et al.Evaluation of earth fissures based on GA-ANN coupling model in the Suzhou-Wuxi-Changzhou area[J].Hydrogeology & Engineering Geology,2008,35(4):106-110.
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基于GA-ANN的苏锡常地裂缝危险性评价()
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《水文地质工程地质》[ISSN:1000-3665/CN:11-2202/P]

卷:
35卷
期数:
2008年4期
页码:
106-110
栏目:
OA栏目
出版日期:
2008-07-15

文章信息/Info

Title:
Evaluation of earth fissures based on GA-ANN coupling model in the Suzhou-Wuxi-Changzhou area
作者:
朱锦旗;焦珣;于军;武健强;苏小四;
中国地质大学,吉林大学环境与资源学院,江苏省地质调查研究院,江苏省地质调查研究院,吉林大学环境与资源学院 武汉430074江苏省地质调查研究院,南京210018,长春130026,南京210018,南京210018,长春130026
Author(s):
ZHU Jin-qi12JIAO Xun3YU Jun2WU Jian-qiang2SU Xiao-si3
1.China University of Geosciences,Wuhan 430074,China;2.Geological Survey of Jiangsu Province,Nanjing 210018,China;3.College of Environment and Resources,Jilin University,Changchun 130026,China
关键词:
地裂缝地面沉降人工神经网络遗传算法苏锡常地区
Keywords:
earth fissures land subsidence ANN GA Suzhou-Wuxi-Changzhou area
分类号:
P642.2
文献标志码:
A
摘要:
文章以苏锡常地区地裂缝危险性评价为例,利用遗传算法(GA)对人工神经网络(ANN)进行改进,先用GA优化BP网络初始权重,再用BP算法修改网络权重,实现不同尺度的同步调整。选择30点的不同地质条件组成样本对所建模型进行训练,评价指标包括:基岩埋深、基岩起伏度、地下水位、地面沉降梯度、含水层导水系数和粘性土层厚度。经过500次GA迭代,得到苏锡常地区地裂缝ANN模型的最佳权重组合,该耦合模型能对全区地裂缝地质条件进行正确分类,精度接近1‰。
Abstract:
Although the ANN(artificial neural network) method has displayed some potential on the earth fissures assessment,the converging problem of the simulation procedure at local proximity is still existing.The genic arithmetic(GA) is more suitable for whole-scale search than for finding local exact key.Thus,they should be improved by each other.In this article,a model set up by coupling GA and ANN is used to evaluate the hazard of earth fissures in the Suzhou-Wuxi-Changzhou area.On the one hand,the i...

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备注/Memo

备注/Memo:
基金:国土资源大调查项目“苏锡常地区地面沉降监测与风险管理”(1212010641203)
更新日期/Last Update: 2008-07-15