Kimura Nobuaki 木村延明

… Alternative Names

KIMURA NOBUAKI 木村延明

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Researcher Number	40706842
Other IDs
Affiliation (Current)	2025: 西九州大学, デジタル社会共創学環, 准教授
Affiliation (based on the past Project Information) *help	2021 – 2023: 国立研究開発法人農業・食品産業技術総合研究機構, 農村工学研究部門, 上級研究員 2020: 九州大学, 工学研究院, 学術研究員 2016 – 2017: 九州大学, 工学研究院, 学術研究員 2014 – 2015: 九州大学, 工学(系)研究科(研究院), 学術研究員
Review Section/Research Field	Principal Investigator Basic Section 41030:Rural environmental engineering and planning-related / Hydraulic engineering Except Principal Investigator Basic Section 41030:Rural environmental engineering and planning-related / Environmental dynamic analysis
Keywords	Principal Investigator データ補完技術 / 排水管理 / 少ない量のデータ / 転移学習 / 物理モデル / 水位予測手法 / 深層学習 / 少ないデータ量 / 流木累積 / 河川洪水 … More / 流木 / 橋梁 / 粒子法 / 流木集積 / 洪水モデル … More Except Principal Investigator リアルタイム / 画像認識 / ANNモデル / 流出予測モデル / 水銀動態 / 北スラベシ / 底泥 / 金鉱山 / メチル水銀 / スラヴェシ島 / 水銀動態モデル / 水銀 Less

Development of an integrated method between deep learning and physical models in lowland drainage management with insufficient observed dataPrincipal Investigator
- Principal Investigator
  
  Kimura Nobuaki
- Project Period (FY)
  2021 – 2023
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 41030:Rural environmental engineering and planning-related
- Research Institution
  National Agriculture and Food Research Organization
Development of a real-time flood forecasting model for low-lying area based on observed water levels and short-term precipitation forecasts
- Principal Investigator
  
  Yoshinaga Ikuo
- Project Period (FY)
  2021 – 2023
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 41030:Rural environmental engineering and planning-related
- Research Institution
  National Agriculture and Food Research Organization
Field survey for modeling of methylmercury dynamics at mercury pollution hotspot from gold mining
- Principal Investigator
  
  Yano Shinichiro
- Project Period (FY)
  2017 – 2019
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Research Field
  
  Environmental dynamic analysis
- Research Institution
  Kyushu University
Development of the SPH model for flooding at a bridgePrincipal Investigator
- Principal Investigator
  
  KIMURA NOBUAKI
- Project Period (FY)
  2014 – 2016
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Research Field
  
  Hydraulic engineering
- Research Institution
  Kyushu University

All 2024 2023 2022 2021 2016 2015 2014 Other

All Journal Article Presentation

[Journal Article] CREATION AND VERIFICATION OF A PRETRAINED MODEL FOR RIVER FLOOD PREDICTIONS2024
- Author(s)
  木村延明，皆川裕樹，福重雄大，馬場大地
- Journal Title
  
  Japanese Journal of JSCE
  
  Volume: 80 Issue: 16 Pages: n/a
- DOI
  10.2208/jscejj.23-16147
- ISSN
  2436-6021
- Language
  Japanese
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K05838, KAKENHI-PROJECT-21H02310
[Journal Article] WATER LEVEL PREDICTIONS THAT VISUALIZE UNCERTAINTY USING LSTM COUPLED WITH ALTERNATIVE METHODS IN BAYESIAN INFERENCE AT A RESERVOIR NEAR A DRAINAGE PUMPING STATION2024
- Author(s)
  木村延明，皆川裕樹，福重雄大，吉永育生，馬場大地
- Journal Title
  
  Japanese Journal of JSCE
  
  Volume: 80 Issue: 22 Pages: n/a
- DOI
  10.2208/jscejj.23-22011
- ISSN
  2436-6021
- Language
  Japanese
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K05838, KAKENHI-PROJECT-21H02310
[Journal Article] Examining practical applications of a neural network model coupled with a physical model and transfer learning for predicting an unprecedented flood at a lowland drainage pumping station2023
- Author(s)
  Kimura Nobuaki、Minakawa Hiroki、Kimura Masaomi、Fukushige Yudai、Baba Daichi
- Journal Title
  
  Paddy and Water Environment
  
  Volume: 21(4) Issue: 4 Pages: 509-521
- DOI
  10.1007/s10333-023-00944-8
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K05838
[Journal Article] GENERATING AN AI PRETRAINED MODEL FOR FLOOD PREDICTIONS USING TRANSFER LEARNING2023
- Author(s)
  木村延明、皆川裕樹、福重雄大、馬場大地
- Journal Title
  
  Advances in River Engineering
  
  Volume: 29 Issue: 0 Pages: 79-84
- DOI
  10.11532/river.29.0_79
- ISSN
  2436-6714
- Language
  Japanese
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-21K05838, KAKENHI-PROJECT-21H02310
[Journal Article] A sophisticated model for riverine-flood predictions using convolutional LSTM and transfer learning2023
- Author(s)
  木村延明、皆川裕樹、福重雄大、吉永育生、馬場大地
- Journal Title
  
  Artificial Intelligence and Data Science
  
  Volume: 4 Issue: 3 Pages: 361-368
- DOI
  10.11532/jsceiii.4.3_361
- ISSN
  2435-9262
- Language
  Japanese
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-21K05838, KAKENHI-PROJECT-21H02310
[Journal Article] PROPOSING A PRE-PROCESSING THAT CONTRIBUTES TO THE ACCURACY IMPROVEMENT OF LSTM WATER LEVEL PREDICTIONS WITH EXTRACTED, PERIODICAL DATA2022
- Author(s)
  木村延明、吉永育生、皆川裕樹、福重雄大、馬場大地
- Journal Title
  
  Intelligence, Informatics and Infrastructure
  
  Volume: 3 Issue: J2 Pages: 85-91
- DOI
  10.11532/jsceiii.3.J2_85
- ISSN
  2435-9262
- Language
  Japanese
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-21H02310
[Journal Article] EVALUATION OF A WATER-LEVEL PREDICTION MODEL THAT EMPLOYS SUPPORT VECTOR REGRESSION IN WATER & DRAINAGE MANAGEMENT2022
- Author(s)
  木村延明, 皆川裕樹, 福重雄大, 馬場大地
- Journal Title
  
  Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)
  
  Volume: 78 Issue: 2 Pages: I_139-I_144
- DOI
  10.2208/jscejhe.78.2_I_139
- ISSN
  2185-467X
- Language
  Japanese
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K05838
[Journal Article] WATER LEVEL PREDICTIONS IN A DRAINAGE PUMPING STATION USING A DEEP LEARNING MODEL, COUPLED WITH A PHYSICAL MODEL AND A TRANSFER LEARNING APPROACH2021
- Author(s)
  木村延明, 皆川裕樹, 福重雄大, 木村匡臣, 馬場大地
- Journal Title
  
  Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)
  
  Volume: 77 Issue: 2 Pages: I_319-I_324
- DOI
  10.2208/jscejhe.77.2_I_319
- NAID
  130008160116
- ISSN
  2185-467X
- Language
  Japanese
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K05838
[Journal Article] Effective dam use for flood control during a heavy rainfall event2016
- Author(s)
  Kimura, N. et al.
- Journal Title
  
  In proceedings of the 12th International Conference of the International Institute for Infrastructure Resilience and Reconstruction
  
  Volume: 12 Pages: 183-190
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PROJECT-26420499
[Journal Article] Assessment of a key factor for mechanism of a river flood, caused by driftwood accumulation at a bridge2015
- Author(s)
  Kimura, N., A. Tai, and A. Hashimoto
- Journal Title
  
  Proceedings of the 11th International Conference of the International Institute for Infrastructure Resilience and Reconstruction (I3R2), CD-ROM, Aug. 27-28, 2015, Seoul, South Korea
  
  Volume: NA
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PROJECT-26420499
[Journal Article] Simulation of driftwood-induced flooding during high-intensity rainfall using smoothed particle hydrodynamics method2014
- Author(s)
  Kimura, N., A. Tai, A. Hashimoto
- Journal Title
  
  土木学会論文集A2分冊 [応用力学]
  
  Volume: Vol. 70, No. 2 Pages: 777-783
- NAID
  130004961373
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PROJECT-26420499
[Journal Article] A flow simulation of a bridge-induced flood in a river using smoothed-particle hydrodynamics (SPH) method2014
- Author(s)
  Kimura, N., A. Tai
- Journal Title
  
  Proceedings of the 19th IAHR-APD Congress (CD-ROM)
  
  Volume: NA
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PROJECT-26420499
[Presentation] ベイズ推定の近似手法を用いた不確実性を考慮したニューラルネットワーク予測モデルの基礎的検討2023
- Author(s)
  木村延明
- Organizer
  農業農村工学会応用水理研究部会（R5年度講演会）
- Data Source
  KAKENHI-PROJECT-21K05838
[Presentation] 排水機場遊水地のAI水位予測の高度化2023
- Author(s)
  木村延明
- Organizer
  山口大学グローカル環境・防災学研究会、第3回「建設分野におけるAI活用の最前線」
- Invited
- Data Source
  KAKENHI-PROJECT-21K05838
[Presentation] Generating an AI-based pretraining flood database (AI-flood DB) using a transfer learning approach2023
- Author(s)
  Nobuaki KIMURA
- Organizer
  Asia Oceania Geosciences Society (AOGS) 2023, Singapore
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K05838
[Presentation] 転移学習を用いた河川洪水イベントの事前学習モデルの構築と検証2023
- Author(s)
  木村延明
- Organizer
  農業農村工学会（2023年度大会講演会）
- Data Source
  KAKENHI-PROJECT-21K05838
[Presentation] An inexperienced flood prediction at a drainage pumping station in lowland using an advanced neural network model, coupled with a physical model and transfer learning.2022
- Author(s)
  Nobuaki KIMURA & Hiroki MINAKAWA
- Organizer
  PAWEES International Conference 2022
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K05838
[Presentation] 層学習に物理モデルを結合させた排水機場水位予測手法の構築2021
- Author(s)
  木村延明，皆川裕樹，福重雄大，馬場大地
- Organizer
  第70回農業農村工学会大会講演会
- Data Source
  KAKENHI-PROJECT-21K05838
[Presentation] Effective dam use for flood control during a heavy rainfall event2016
- Author(s)
  Kimura, N.
- Organizer
  The 12th International Conference of the International Institute for Infrastructure Resilience and Reconstruction
- Place of Presentation
  Kandy, Sri Lanka
- Year and Date
  2016-08-05
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26420499
[Presentation] Assessment of a key factor for mechanism of a river flood, caused by driftwood accumulation at a bridge2015
- Author(s)
  Kimura N.
- Organizer
  The 11th International Conference of the International Institute for Infrastructure Resilience and Reconstruction (I3R2)
- Place of Presentation
  Seoul, South Korea
- Year and Date
  2015-08-28
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26420499
[Presentation] A flow simulation of a bridge-induced flood in a river using smoothed-particle hydrodynamics (SPH) method
- Author(s)
  Kimura, N
- Organizer
  The 19th IAHR-APD Congress
- Place of Presentation
  Hanoi, Vietnam
- Year and Date
  2014-09-22 – 2014-09-24
- Data Source
  KAKENHI-PROJECT-26420499
[Presentation] 流木を伴う橋梁部における洪水現象の数値シミュレーション
- Author(s)
  木村延明, 田井明
- Organizer
  平成26年度土木学会全国大会第69回年次学術講演会
- Place of Presentation
  大阪大学，大阪
- Year and Date
  2014-09-10 – 2014-09-12
- Data Source
  KAKENHI-PROJECT-26420499

1. Tai Akira (20585921)

# of Collaborated Projects: 2 results

# of Collaborated Products: 4 results
2. Yano Shinichiro (80274489)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
3. Yoshinaga Ikuo (50414420)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
4. 松山明人 (00393463)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
5. 中田達 (10584336)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
6. 島崎昌彦 (30355135)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
7. 皆川裕樹 (70527019)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
8. 福重雄大 (80845850)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results

Kimura Nobuaki 木村 延明

KIMURA NOBUAKI 木村 延明

Research Projects

Research Products

Co-Researchers

Development of an integrated method between deep learning and physical models in lowland drainage management with insufficient observed dataPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of a real-time flood forecasting model for low-lying area based on observed water levels and short-term precipitation forecasts

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Field survey for modeling of methylmercury dynamics at mercury pollution hotspot from gold mining

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

Development of the SPH model for flooding at a bridgePrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

[Journal Article] CREATION AND VERIFICATION OF A PRETRAINED MODEL FOR RIVER FLOOD PREDICTIONS2024

Author(s)

Journal Title

DOI

ISSN

Language

Data Source

[Journal Article] WATER LEVEL PREDICTIONS THAT VISUALIZE UNCERTAINTY USING LSTM COUPLED WITH ALTERNATIVE METHODS IN BAYESIAN INFERENCE AT A RESERVOIR NEAR A DRAINAGE PUMPING STATION2024

Author(s)

Journal Title

DOI

ISSN

Language

Data Source

[Journal Article] Examining practical applications of a neural network model coupled with a physical model and transfer learning for predicting an unprecedented flood at a lowland drainage pumping station2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] GENERATING AN AI PRETRAINED MODEL FOR FLOOD PREDICTIONS USING TRANSFER LEARNING2023

Author(s)

Journal Title

DOI

ISSN

Language

Data Source

[Journal Article] A sophisticated model for riverine-flood predictions using convolutional LSTM and transfer learning2023

Author(s)

Journal Title

DOI

ISSN

Language

Data Source

[Journal Article] PROPOSING A PRE-PROCESSING THAT CONTRIBUTES TO THE ACCURACY IMPROVEMENT OF LSTM WATER LEVEL PREDICTIONS WITH EXTRACTED, PERIODICAL DATA2022

Author(s)

Journal Title

DOI

ISSN

Language

Data Source

[Journal Article] EVALUATION OF A WATER-LEVEL PREDICTION MODEL THAT EMPLOYS SUPPORT VECTOR REGRESSION IN WATER &amp; DRAINAGE MANAGEMENT2022

Author(s)

Journal Title

DOI

ISSN

Language

Data Source

[Journal Article] WATER LEVEL PREDICTIONS IN A DRAINAGE PUMPING STATION USING A DEEP LEARNING MODEL, COUPLED WITH A PHYSICAL MODEL AND A TRANSFER LEARNING APPROACH2021

Author(s)

Journal Title

DOI

Kimura Nobuaki 木村延明

KIMURA NOBUAKI 木村延明

[Journal Article] EVALUATION OF A WATER-LEVEL PREDICTION MODEL THAT EMPLOYS SUPPORT VECTOR REGRESSION IN WATER & DRAINAGE MANAGEMENT2022