Ryugaku Jinja · Professor Archive
Public Professor Archive
Nobuyuki Egusa江種 伸之
Wakayama University · Faculty of Systems Engineering · 教授
- Publications
- 4
- Projects
- 2
- Keywords
- 3
留学
神社Wakayama University · Faculty of Systems Engineering · 教授
Research keywords地盤災害・流域水問題・土壌地下水汚染
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- Building a Generalized Pre-Training Model to Predict River Water-Level from Radar Rainfall2025 · In our previous work, we proposed a river water-level prediction method using deep learning, incorporating radar rainfall data in place of water-level and rainfall stations upstream of the prediction point. By introducing a newly defined flow distance matrix, transfer learning becomes available, i.e., even when data at the prediction point is scarce, accurate water-level predictions are made using inundation data from other rivers. However, this approach requires pre-selecting rivers that behave similarly to the prediction point for training, making it laborious to build prediction models for multiple rivers. Furthermore, the previous study only performed predictions for a single river, raising uncertainty about whether the method is applicable to water-level prediction for other rivers with different conditions. In this paper, we construct a generalized river water-level prediction model commonly applicable to multiple Japanese rivers by using inundation data from all Japanese Class-A rivers (the major river systems managed by the government) for pre-training, rather than only the rivers similar to the prediction site. Through evaluation, we showed that pre-training using all Class-A rivers yields higher prediction accuracy than pre-training using similar rivers across multiple rivers with varying conditions. This demonstrates that using all Class-A rivers for pre-training enables the construction of a generalized river water-level prediction model applicable to a wide range of rivers.
- PFAS汚染土壌の不溶化処理に伴う長期安定性に関する評価2025 · 日野良太, 西川直仁, 日笠山徹巳, 江種伸之 (担当区分: 最終著者 )
- 水理公式集例題集(2024年版)2024 · 土木学会( 担当: 分担執筆, 担当範囲: 例題1.24,例題1.26)
- A Transfer Learning Approach Based on Radar Rainfall for River Water-Level Prediction2024 · Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa, Takuya Yoshihiro
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