Consideration of XAI in Inflow Prediction Model Using Convolutional Neural Network
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- HAKOISHI Kenta
- 日本工営株式会社 中央研究所
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- HITOKOTO Masayuki
- 日本工営株式会社 中央研究所
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- ZENKOJI Shingo
- 日本工営株式会社 中央研究所
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- NISHIGUCHI Ryota
- 日本工営株式会社 河川水資源事業部 河川部
Bibliographic Information
- Other Title
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- 畳み込みニューラルネットワークを用いた流入量予測モデルにおけるXAIの考察
Abstract
<p>With the development of AI technology, various inflow prediction methods have been proposed, but to increase reliability and realize social implementation, it is necessary to show the grounds leading up to prediction and ensure the validity of the prediction results. In this study, the target basin is the Gonokawa Haji dam basin, and an inflow prediction model was constructed using a convolutional neural network with the radar-raingauge analyzed precipitation of the Japan Meteorological Agency as the input condition. We applied XAI (explainable AI) technology to this model and visualized and considered the basis of the pre- diction. As a result of the consideration, the validity of the inflow prediction model was confirmed.</p>
Journal
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- Artificial Intelligence and Data Science
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Artificial Intelligence and Data Science 4 (3), 539-546, 2023
Japan Society of Civil Engineers
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Details 詳細情報について
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- CRID
- 1390016649288764928
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- ISSN
- 24359262
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed