The 69th Conference on Hydraulic Engineering
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Oral_Session_Hydrology / Water resources

[S18]Application of machine learning to hydrology

Tue. Dec 3, 2024 1:45 PM - 3:45 PM JST
Tue. Dec 3, 2024 4:45 AM - 6:45 AM UTC
Room2(Meeting Room 304)
Chair1:RYO MORIWAKI Chair2:TAKEHIKO ITO
1:45 PM - 2:00 PM JST(4:45 AM - 5:00 AM UTC)

[104]RELIABILITY ESTIMATION OF 6-MONTH PRECIPITATION PREDICTION IN ASIAN MONSOON REGION USING DEEP LEARNING

*Kiyoharu KAJIYAMA1, Shinjiro KANAE2 (1. 東京工業大学 土木・環境工学系、2. 東京工業大学 土木・環境工学系)
2:00 PM - 2:15 PM JST(5:00 AM - 5:15 AM UTC)

[105]MACHINE LEARNING APPROACH ON INPUT VARIABLE SELECTION FOR MONTHLY RAINFALL PREDICTION CONSIDERING TELECONNECTIONS

*Sirada JONGWATTANAPAIBOON1, Sunmin KIM2, Yasuto TACHIKAWA3 (1. Dept. of Civil and Earth Resources Eng., Kyoto University、2. Dept. of Civil and Earth Resources Eng., Kyoto University、3. Dept. of Civil and Earth Resources Eng., Kyoto University)
2:15 PM - 2:30 PM JST(5:15 AM - 5:30 AM UTC)

[106]EVALUATING THE PRECIPITATION PREDICTION SKILL BY GRAPHCAST IN THE JAPAN REGION

*Ryosuke ARAI1, Takahiro SATO1, Masahiro IMAMURA1 (1. (一財)電力中央研究所)
2:30 PM - 2:45 PM JST(5:30 AM - 5:45 AM UTC)

[通常号1]INVESTIGATION ON ACCURATE PREDICTION OF WATER LEVEL IN A SMALL-MEDIUM SIZED RIVER BASIN USING DEEP LEARNING土木学会論文集，Vol.79，No.8，22-00234，2023

Daichi FUKUMARU  (co-author: Yoshihisa AKAMATSU, Tetsuya SHINTANI)
2:45 PM - 3:00 PM JST(5:45 AM - 6:00 AM UTC)

[107]A STUDY ON DEEP LEARNING FOR RIVER WATER LEVEL PREDICTION IN URBAN WATERSHEDS WITH A DISCUSSION ON UNDERGROUND REGULATING RESERVOIR GATE OPERATIONS

*Cabila SUBRAMANIYAM1, Hideo AMAGUCHI2, Yoshiyuki IMAMURA3 (1. Dept. of Civil Eng., Tokyo Metropolitan University、2. Dept. of Civil Eng., Tokyo Metropolitan University、3. Dept. of Civil Eng., Tokyo Metropolitan University)
3:00 PM - 3:15 PM JST(6:00 AM - 6:15 AM UTC)

[108]IMPROVEMENT OF WATER LEVEL PREDICTION USING NEURAL NETWORK BY SPATIAL SEGMENTATION OF RAINFALL

*Go OHNO1, Yukinobu ODA2, Takahiro SAYAMA3 (1. 大成建設株式会社 技術センター、2. 大成建設株式会社 技術センター、3. 京都大学 防災研究所)
3:15 PM - 3:30 PM JST(6:15 AM - 6:30 AM UTC)

[109]COMPARISON OF ACCURACY BETWEEN LSTM AND FEEDFORWARD NEURAL NETWORKS IN PREDICTION OF DAM INFLOW

*Yuto ENDO1, Masayuki HITOKOTO2, Yoshihiro NISHITO3 (1. 日本工営株式会社、2. 日本工営株式会社 中央研究所、3. 日本工営エナジーソリューションズ株式会社 福島事業所)
3:30 PM - 3:45 PM JST(6:30 AM - 6:45 AM UTC)

General discussion

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