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智能流域管理的关键问题与模型技术
引用本文:邹锐,刘永,颜小品,郭怀成.智能流域管理的关键问题与模型技术[J].北京大学学报(自然科学版),2011(5):868-874.
作者姓名:邹锐  刘永  颜小品  郭怀成
作者单位:Tetra Tech Inc;昆明诚锐环保科技有限公司;北京大学环境科学与工程学院水沙科学教育部重点实验室;
基金项目:国家水体污染控制与治理科技重大专项(2008ZX07102-001)资助
摘    要:在总结流域问题现状及流域管理决策需求的基础上,基于仿生学原理,类比人的思维特征和决策过程,提出了包括流域信息获取、输入-输出因果关联模拟以及优化决策等步骤在内的智能流域管理模式,并对比分析了智能流域管理和传统流域管理的差异性。提出了智能流域管理的4个关键问题:管理目标的确定、基于智能因子关联与流动的模型开发与信息获取、...

关 键 词:智能流域管理  决策  模拟-优化  不确定性

Key Components and Modeling Framework for Intelligent Watershed Management (IWM)
ZOU Rui,LIU Yong,YAN Xiaopin,GUO Huaicheng .Tetra Tech,Inc. Eaton Place,Ste ,Fairfax,VA ,.College of Environmental Science , Engineering,Key Laboratory of Water , Sediment Sciences,Peking University,Beijing ,.Kunming Challenger Technology Inc.,Kunming.Key Components and Modeling Framework for Intelligent Watershed Management (IWM)[J].Acta Scientiarum Naturalium Universitatis Pekinensis,2011(5):868-874.
Authors:ZOU Rui    LIU Yong  YAN Xiaopin  GUO Huaicheng Tetra Tech  Inc Eaton Place  Ste  Fairfax  VA  College of Environmental Science  Engineering  Key Laboratory of Water  Sediment Sciences  Peking University  Beijing  Kunming Challenger Technology Inc  Kunming
Institution:ZOU Rui1,3,LIU Yong2,YAN Xiaopin2,GUO Huaicheng2 1.Tetra Tech,Inc.10306 Eaton Place,Ste 340,Fairfax,VA 22030,2.College of Environmental Science and Engineering,Key Laboratory of Water and Sediment Sciences(MOE),Peking University,Beijing 100871,3.Kunming Challenger Technology Inc.,Kunming 650021
Abstract:A new watershed management module,Intelligent Watershed Management(IWM),was proposed.The decision need for watershed management was analyzed before the conception and components of IWM were formulated.The idea of IWM comes from the principles of bionics and imitates the process of human decisions.The IWM is significantly differing from traditional watershed management,which includes three main steps,i.e.watershed information inquiring,input-output response modeling at the watershed scale,and optimized decis...
Keywords:intelligent watershed management  decision making  simulation-optimization  uncertainty  
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