Oral_Session_ cross-disciplinary approaches

[S21] Machine learning

Wed. Dec 13, 2023 9:30 AM - 11:30 AM Room5 (Seminar Room 6AB)

Chair:MASAYUKI HITOKOTO Chair2:Ryo Kaneko(Chiba University)

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9:30 AM - 9:45 AM

[147] CREATION AND VERIFICATION OF A PRETRAINED MODEL FOR RIVER FLOOD PREDICTIONS

*Nobuaki KIMURA¹, Hiroki MINAKAWA², Yudai FUKUSHIGE², Daichi BABA³ (1. 農研機構農村工学研究部門、2. 農研機構農村工学研究部門、3. ㈱アーク情報システムアドバンストテクノロジー部)

9:45 AM - 10:00 AM

[148] DAM INFOLOW FORECASTING IN THAILAND USING A PRE-TRAINED TRANSFORMER MODEL

*Daiki TOGI¹, Kiyoharu KAJIYAMA², Shinjiro KANAE³ (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、3. 東京工業大学土木・環境工学系)

10:00 AM - 10:15 AM

[149] IMPROVEMENT OF DEEP LEARNING RAINFALL FORECAST AND DETAILED EVALUATION

*Ryo KANEKO¹, Kei YOSHIMURA² (1. 東京大学生産技術研究所、2. 東京大学生産技術研究所)

10:15 AM - 10:30 AM

[150] DEEP LEARNING OF UNDERWATER IMAGES AND TRAINING DATA CRITERIA FOR UNDERSTANDING FEEDING INJURY OF ACANTHOPAGRUS SCHLEGELII IN NORI SEAWEED FARMS

Keisuke YOSHIDA¹, Shijun PAN², Takahiro YOKOYAMA³, Yasushi YAMASHITA³, *Yuki UEDA², Hiroyuki SUGINO³, Takashi KOJIMA⁴ (1. 岡山大学学術研究院環境生命自然科学学域、2. 岡山大学大学院環境生命科学研究科、3. 岡山県農林水産総合センター水産研究所、4. 株式会社東京建設コンサルタント環境防災研究所)

10:30 AM - 10:45 AM

[151] ANNUAL PAST-PRESENT LAND COVER CLASSIFICATION FROM LANDSAT USING DEEP LEARNING FOR URBAN AGGLOMERATIONS

*Worameth CHINCHUTHAKUN¹, David WINDERL², Alvin C.G. VARQUEZ³, Yukihiko YAMASHITA⁴, Manabu KANDA⁵ (1. Dept. of Transdisciplinary Sci. and Eng., Tokyo Institute of Technology, 2. CIT Dept. of Computer Science, Technical University of Munich, 3. Dept. of Transdisciplinary Sci. and Eng., Tokyo Institute of Technology, 4. Center for Innovative Teaching and Learning, Tokyo Institute of Technology, 5. Dept. of Transdisciplinary Sci. and Eng., Tokyo Institute of Technology)

10:45 AM - 11:00 AM

[152] MACHINE LEARNING ON GCM ATMOSPHERIC VARIABLES FOR SPATIAL DOWNSCALING OF PRECIPITATION

*Sunmin KIM¹, Masaharu SHIBATA², Yasuto TACHIKAWA³ (1. Dept. of Civil and Earth Resources Eng., Kyoto University, 2. P&S ITS Division, Global Technology Solution BG, Fujitsu Ltd., 3. Dept. of Civil and Earth Resources Eng., Kyoto University)

11:00 AM - 11:15 AM

[153] APPLICATION OF RADIAL-BASIS FUNCTION NETWORK TO CHARACTERIZE FUTURE RAINFALL PRONE TO SEDIMENT HAZARDS IN A CHANGING CLIMATE

*Ying-Hsin WU¹, Akihiko YAMAJI², Eiichi NAKAKITA³ (1. Disaster Prevention Research Institute, Kyoto University, 2. Disaster Prevention Research Institute, Kyoto University, 3. Disaster Prevention Research Institute, Kyoto University)

General discussion (11:15 AM - 11:30 AM)

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