淡江大學機構典藏:Item 987654321/67870
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    题名: Real-Time Reservoir Operation for Flood Control Using Artificial Intelligent Techniques
    作者: Chang, Li-Chiu;Chang, Fi-John;Hsu, Hung-Cheng
    贡献者: 淡江大學水資源及環境工程學系
    关键词: Reservoir flood control;Adaptive network-based fuzzy inference system;ANFIS;Genetic algorithm;GA;Real-time decision-making process
    日期: 2011-05
    上传时间: 2011-10-23 02:09:53 (UTC+8)
    出版者: Berlin: Walter de Gruyter GmbH & Co. KG
    摘要: Real-time reservoir operation for flood control is a continuous and instant decision-making process based on relevant operating rules, in addition to the immediate rainfall and hydrological information. To reduce downstream flood peak stage and store floodwaters for future use, reservoir operational for flood control plays a critical role. The aim of this study is to establish a real-time reservoir operational model, the intelligent fuzzy flood control model (IFFCM), for flood control to ensure reservoir safety and store floodwaters for future use. The model includes two major artificial intelligent processes: knowledge acquirement and implementation, and fuzzy inference system. The IFFCM is first built by extracting the knowledge from the optimal operating hydrographs of typhoon events obtained by genetic algorithm (GA) and is then inferred reservoir release by the adaptive network-based fuzzy inference system (ANFIS). The Shihmen Reservoir in northern Taiwan is used as a case study with particular attention to the operations of 26 flood events by the proposed method. The results demonstrate that the proposed model can perform much better than historical reservoir operations and effectively reduce downstream peak flood stage and store floodwaters for future use.
    關聯: International Journal of Nonlinear Sciences and Numerical Simulation 11(11), pp.887-902
    DOI: 10.1515/IJNSNS.2010.11.11.887
    显示于类别:[水資源及環境工程學系暨研究所] 期刊論文

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