paper
2021
Extremes & hazards
Climate analysis & attribution Evaluation or intercomparison of existing models
Classical ML (trees, GP, linear, kernels) Preprint
2021-06-17
004
Jun 2021
Felix Obi Ohanuba, Mohd Tahir Ismail, Majid Khan Majahar Ali et al.
Research Square
Unsupervised topological data analysis is used to identify atmospheric river patterns linked to flooding in Nigeria; no abstract is available.
On the Cluster Validity Test (s) in Unsupervised Machine Learning TDA Approach for Atmospheric River Patterns on Flood Detection in Nigeria
In one sentence. Unsupervised topological data analysis is used to identify atmospheric river patterns linked to flooding in Nigeria; no abstract is available.
Labels
- Topic
- Extremes & hazards, Climate analysis & attribution
- Type
- Evaluation or intercomparison of existing models
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- ERA5 / reanalysis
- Status
- Research
- Identifiers
- DOI:10.21203/rs.3.rs-459258/v1 OpenAlex:W3167341067
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.