River Flood Disaster Prediction in the Matsue City using Gaussian Process Auto Regression
Matsue City has a complex network of natural and artificial rivers, shaped by historical factors, which occasionally leads to serious flood disasters. To address this issue, we developed a flood prediction model using Gaussian Process Auto Regression (GPAR). The results of this study demonstrate that the GPAR model provides strong predictive performance for flood events in this region.
Authors
- Ryo Takagi (ORCID: https://orcid.org/0000-0002-5930-0329)
- Katsuzo Wakabayashi
- Hiroshi Yajima (ORCID: https://orcid.org/0000-0002-0361-1080)
- Hitoshi Sakano
Institutions
- Shimane University (JP)
Publication Details
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1109/icct-pacific63901.2025.11012785
- Primary Topic
- Technology and Data Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00