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EMULATION OF URBAN RUNOFF MODEL BY DEEP LEARNING FOR BENCHMARK VIRTUAL HYETO AND HYDROGRAPH
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- FUJIZUKA Shintaro
- 東京都 建設局 江東治水事務所
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- KAWAMURA Akira
- 首都大学東京 都市環境科学研究科
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- AMAGUCHI Hideo
- 首都大学東京 都市環境科学研究科
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- TAKASAKI Tadakatsu
- 東京都 土木技術支援・人材育成センター
Bibliographic Information
- Other Title
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- ベンチマークバーチャルハイエト・ハイドログラフを用いた深層学習による都市流出モデルのエミュレーション
Description
<p> In recent years, flood disaster in urban area have frequently occurred, and improving the accuracy of urban runoff prediction is a pressing issue. The urban runoff mechanism is complicated, and it is difficult to constract an accurate prediction model. So, in this paper, we aim to confirm whether the urban runoff model can be emulated by using the deep learning model, first of all, runoff volume (virtual hydrograph) using the urban runoff model and virtual rainfall (virtual hyetograph) was constructed. Then, using the created virtual hyetograph and virtual hydrograph, we constructed a deep neural network model and verified the reproducibility in the training data and the validation data. In addition, since the observation data of floods used as input data is limited, the reproduction characteristics when the number of training data was reduced were examined.</p>
Journal
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- Journal of Japan Society of Civil Engineers, Ser. G (Environmental Research)
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Journal of Japan Society of Civil Engineers, Ser. G (Environmental Research) 75 (5), I_289-I_296, 2019
Japan Society of Civil Engineers
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Keywords
Details 詳細情報について
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- CRID
- 1390846609819352832
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- NII Article ID
- 130007821948
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- ISSN
- 21856648
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed