Estimation of Tidal Energy Potential and Identification of Hotspots Using Random Forest
Tide tables are used to forecast high and low tide heights. This phenomenon is highly predictable, and current velocities are proportional to tide heights. Therefore, this work aims to correlate current velocity and direction data with tide height at a given moment and apply these data to a Random Forest machine learning model to predict current velocities up to 6 days in advance.
Authors
- Rafael B. S. Veras (ORCID: https://orcid.org/0000-0001-8298-7045)
- Norton Borges Júnior
- Shigeaki Leite de Lima
- Denivaldo Lopes (ORCID: https://orcid.org/0000-0002-4217-1399)
Institutions
- Universidade Federal do Maranhão (BR)
Publication Details
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1109/urucon63440.2024.10850421
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico