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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/67846


    Title: Intelligent control for modelling or real-time reservoir operation
    Authors: 張麗秋;Chang, Li-chiu;Chang, Fi-john
    Contributors: 淡江大學水資源及環境工程學系
    Date: 2001-06-01
    Issue Date: 2011-10-23 02:07:42 (UTC+8)
    Publisher: Wiley Online
    Abstract: This paper presents a new approach to improving real-time reservoir operation. The approach combines two major procedures: the genetic algorithm (GA) and the adaptive network-based fuzzy inference system (ANFIS). The GA is used to search the optimal reservoir operating histogram based on a given inflow series, which can be recognized as the base of input–output training patterns in the next step. The ANFIS is then built to create the fuzzy inference system, to construct the suitable structure and parameters, and to estimate the optimal water release according to the reservoir depth and inflow situation. The practicability and effectiveness of the approach proposed is tested on the operation of the Shihmen reservoir in Taiwan. The current M-5 operating rule curves of the Shihmen reservoir are also evaluated. The simulation results demonstrate that this new approach, in comparison with the M-5 rule curves, has superior performance with regard to the prediction of total water deficit and generalized shortage index (GSI). Copyright © 2001 John Wiley & Sons, Ltd.
    Relation: Hydrological processes 15(9), pp.1621-1634
    DOI: 10.1002/hyp.226
    Appears in Collections:[Graduate Institute & Department of Water Resources and Environmental Engineering] Journal Article

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