APPLICATION OF DAM OPERATION MODEL USING DEEP REINFORCEMENT LEARNING IN RECENT FLOOD CASES

• HAKOISHI Kenta

  日本工営株式会社 中央研究所

• HITOKOTO Masayuki

  日本工営株式会社 中央研究所

Bibliographic Information

Other Title

• 近年の実洪水事例における深層強化学習を用いたダム操作モデルの適用

Abstract

In this study, we improved and verified the dam operation model using deep reinforcement learning. Previous studies of this model have only verified for the virtual floods, which greatly exceed the design floods, and have not verified their effectiveness during actual floods. In this study, we added condition settings for suppression of over-discharge and improved the reward function based on the problems of the previous model. In addition, by adjusting the flood scale of the learning data used for deep reinforcement learning, we aimed to acquire effective discharge operations for floods of the design scale. We compared the improved dam operation model with the the previous model for recent actual flood case which caused disasters. It was confirmed that the improved model reduced the peak discharge compared to the previous model and was similar to the discharge pattern of the actual dam operation..

Journal

• Intelligence, Informatics and Infrastructure

  Intelligence, Informatics and Infrastructure 2 (J2), 165-171, 2021

  Japan Society of Civil Engineers

Keywords

• flood control
• dam-operation
• deep learning
• reinforcement learning

Details

• CRID: 1390290088582172160
• NII Article ID: 130008118245
• DOI: 10.11532/jsceiii.2.j2_165
• ISSN: 24359262
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed