ニューラルネットワークと回帰式を適用した連接水系ダム残流予測システムの開発
スポンサーリンク
概要
- 論文の詳細を見る
This paper describes a water flow forecasting system for dams using neural networks and regression models. Water flow forecasting task is very important for reliable and economic operation. Many conventional methods have been used. They take much time to develop an accurate forecasting system, because it is difficult to adjust parameters.Water flow forecasting system for dams, which have much flood data, can be developed by neural networks. On the contrary, that system for dams, which have few flood data, must be developed by regression models. The system has been used for three years at Tadami/Agano river basin to assure forecasting performance by the proposed method.
論文 | ランダム
- 5009 民間分譲住宅居住階層の構成と住居歴(住宅問題・都市計画)
- 5010 民間分譲住宅居住階層の住意識(住宅問題・都市計画)
- 耐久消費財の住生活に与える影響 : 京都市不良住宅地区改良住宅の場合
- 鉄道紀行(その256)大井川鐵道(株)・大井川本線 愛とロマンの大井川鐵道
- 異種材料のレーザ溶接・接合(創立110周年記念,つなぐ,つける,はめる)