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人工神经网络在水源地影响评价中的应用
引用本文:魏加华,李宁,张建立,程凌鹏,张远东,周宏.人工神经网络在水源地影响评价中的应用[J].地球学报,2001,22(3):283-288.
作者姓名:魏加华  李宁  张建立  程凌鹏  张远东  周宏
作者单位:中国地质大学,北京;北京地质工程勘察院;北京大学地质系,北京;中国地质大学,北京;中国地质大学,北京;河石油勘探局供水公司水文地质所,辽宁盘锦
摘    要:为了评价水源地开采过程中对周围地下水环境的影响,本文运用BP神经网络模型建立了有4个输入、2个输出的三层网络模型,通过BP网络学习训练,得到水源地的BP网络模型,并运用该模型预测了在不同条件下因水源地开采所引起的降落漏斗秒地下水补给量,计算表明,BP神经网络用于模拟地下水系统简便,实用,能很好地预测地下水动态变化情况。

关 键 词:BP神经网络    水源地    地下水    评价

The Application of BP Neural Network to the Evaluation of Wellhead Field Influence
WEI Jia-hu,LI Ning,ZHANG Jian-li,CHENG Ling-peng,ZHANG Yuan-dong and ZHOU Hong.The Application of BP Neural Network to the Evaluation of Wellhead Field Influence[J].Acta Geoscientia Sinica,2001,22(3):283-288.
Authors:WEI Jia-hu  LI Ning  ZHANG Jian-li  CHENG Ling-peng  ZHANG Yuan-dong and ZHOU Hong
Institution:China University of Geosciences, Beijng;Beijing Institute of Geological Engineering Exploration, Beijng;Department of Geology, Peking University;China University of Geosciences, Beijng;China University of Geosciences, Beijng;Institute of Hydrogeology, Water Supply Company, Liaohe Bureau of Petroleum Exploration, Panjin, Liaoning
Abstract:In order to evaluate the influence of groundwater pumping on groundwater environment, the authors formulated a model with four input units and two output units by using a three layer BP neural network. The drawdown area caused by pumping and groundwater recharge volume were predicted by the learned and trained BP nerwork. The results of the evaluation show that the application of BP neural network to simulating groundwater system is convenient, precise and satisfactory in predicting groundwater dynamic changes.
Keywords:BP neural network  wellhead field  groundwater  evaluation
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