Research on the Application of Machine Learning Technology in Hydrological Flood Prediction
Urban flooding disasters frequently occur in our country, severely affecting the national development process, anticipating the probability and severity of floods can effectively reduce the negative impacts caused by floods, the rapid progress of hydrology has accelerated the development of flood prediction research. Currently, a lot of machine learning methods are widely applied in the field of flood forecasting based on hydrology, which holds great significance for social development. First, the hydrological models currently used for flood forecasting are introduced. Then, the application of machine learning models in hydrology is elaborated. Finally, the problems and challenges faced by machine learning in flood prediction are analyzed and summarized, and prospects for future flood prediction technologies are discussed.
Authors
- Yuan Gao (ORCID: https://orcid.org/0000-0002-3376-8433)
Institutions
- North China Electric Power University (CN)
Publication Details
- Journal
- Journal of Computer Signal and System Research
- Published
- 2025-03-14
- DOI
- https://doi.org/10.71222/se6cyv71
- Primary Topic
- Computational Physics and Python Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00