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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/44608

    Title: Fuzzy exemplar-based inference system for flood forecasting
    Authors: 張麗秋;Chang, Li-chiu;Chang, Fi-john;Tsai, Ya-hsin
    Contributors: 淡江大學水資源及環境工程學系
    Date: 2005-01
    Issue Date: 2010-03-26 16:30:24 (UTC+8)
    Publisher: American Geophysical Union (AGU)
    Abstract: [1] Fuzzy inference systems have been successfully applied in numerous fields since they can effectively model human knowledge and adaptively make decision processes. In this paper we present an innovative fuzzy exemplar-based inference system (FEIS) for flood forecasting. The FEIS is based on a fuzzy inference system, with its clustering ability enhanced through the Exemplar-Aided Constructor of Hyper-rectangles algorithm, which can effectively simulate human intelligence by learning from experience. The FEIS exhibits three important properties: knowledge extraction from numerical data, knowledge (rule) modeling, and fuzzy reasoning processes. The proposed model is employed to predict streamflow 1 hour ahead during flood events in the Lan-Yang River, Taiwan. For the purpose of comparison the back propagation neural network (BPNN) is also performed. The results show that the FEIS model performs better than the BPNN. The FEIS provides a great learning ability, robustness, and high predictive accuracy for flood forecasting.
    Relation: Water resources research 41(2), pp.1-12
    DOI: 10.1029/2004WR003037
    Appears in Collections:[水資源及環境工程學系暨研究所] 期刊論文

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