広域雨量データを用いたニューラルネットワークによるダム流入量予測 Inflow Forecasting of a Dam by Neural Network Using Rain Data in Wide Area

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At a multipurpose dam, it is necessary to forecast inflow to control flood safely and to operate hydraulic power plant efficiently. In this paper, we propose a method of forecasting the inflow of several hours later by neural network. The correlation is high about the inflow and rain which fell in the dam basin, but it is difficult to forecast by mathematical methods, because the relation is non-linear model. The neural network system can forecast the inflow by learning the past data of inflow and rain in the basin. This system can forecast inflow well after 1 hour or so. However, this system becomes inaccurate rapidly when it tries to forecast inflow at 3 or more hours later, because we use the rain data of the dam basin. Therefore, we also use rain data which is out of the dam basin and in the direction of the windward. The rain data contains information of the rain which will fall at the dam in future. Then, forecast results show that our system is effective.

収録刊行物

  • 電気学会論文誌. B, 電力・エネルギー部門誌 = The transactions of the Institute of Electrical Engineers of Japan. B, A publication of Power and Energy Society

    電気学会論文誌. B, 電力・エネルギー部門誌 = The transactions of the Institute of Electrical Engineers of Japan. B, A publication of Power and Energy Society 124(4), 561-568, 2004-04-01

    The Institute of Electrical Engineers of Japan

参考文献:  8件中 1-8件 を表示

被引用文献:  7件中 1-7件 を表示

各種コード

  • NII論文ID(NAID)
    10012706055
  • NII書誌ID(NCID)
    AN10136334
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    03854213
  • NDL 記事登録ID
    6908992
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-794
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
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