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    Downscaling CGCM Climate Change Output Scenario Using the Artificial Neural Network Model

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    Downscaling CGCM Climate Change Output Scenario Using the Artificial Neural Network Model

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    Downscaling CGCM Climate Change Output Scenario Using the Artificial Neural Network Model

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    Document information
    Title:

    Downscaling CGCM Climate Change Output Scenario Using the Artificial Neural Network Model

    Contributors:

    Boosik, K. (author) / Jeong-Seok, Y. (author) / International Association of Hydraulic Engineering and Research

    Conference:

    Congress; 33rd, International Association of Hydraulic Engineering and Research; Water engineering for a sustainable environment ; 2009 ; Vancouver, Canada

    Published in:

    International Association of Hydraulic Engineering and Research; Water engineering for a sustainable environment ; TS201

    PROCEEDINGS OF THE CONGRESS- INTERNATIONAL ASSOCIATION FOR HYDRAULIC RESEARCH

    Publication date:

    2009-01-01

    Size:

    TS201

    Remarks:

    Collocated with the 19th Canadian Hydrotechnical Conference; Held in e-store (RMS)

    ISBN:

    9789078046080

    Type of media:

    Conference paper

    Type of material:

    Print

    Language:

    English

    Keywords:

    Hydraulic engineering , IAHR , Hydrotechnical

    © Metadata Copyright the British Library Board and other contributors. All rights reserved.

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