AI-based water disaster risk reduction and the understanding of the natural environment
- 2.5 High reliability
- 3.9 Environmental science
- 4.6 Transparency and explainability
Takao Yoshikane
Institute of Industrial Science
Project Associate Professor
The purpose of this project is to build an early warning system by applying high-performance numerical models and high-quality observation data to AI, while also sharing information according to individual situations and needs, thereby significantly reducing the risk of water-related disasters caused by various environmental changes.
The University of Tokyo
Research collaborators
- Kei Yoshimura (The University of Tokyo)
- Gaohang Yin (The University of Tokyo)
- Japan Aerospace Exploration Agency (JAXA)
Related publications
- Takao Yoshikane, Kei Yoshimura, ”Dispersion characteristics of radioactive materials estimated by wind patterns”, Scientific Reports, 8:9926, (2018).
- Takao Yoshikane, Kei Yoshimura, “Development of method of spot weather forecast using machine learning” , Proceedings of the Annual Conference of JSAI, (2019). (In Japanese)
- Takao Yoshikane, Kei Yoshimura, “Estimation of extreme weather event using AI and numerical simulation”, Proceedings of the Annual Conference of JSAI, (2020). (In Japanese)
SDGs
Contact
- Takao Yoshikane
- Tel: +81-4-7136-6965
- Email: takao-y[at]iis.u-tokyo.ac.jp
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