Machine learning-based forecasting of rainfall and water demand for urban water planning: the case of Ekurhuleni, South Africa.
- DOI
- 10.1038/s41598-026-51831-1
- Published
- 2026 May 6
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-51831-1,
title = {Machine learning-based forecasting of rainfall and water demand for urban water planning: the case of Ekurhuleni, South Africa.},
author = {Lomboli MB and Laseinde OT and Aigbavboa CO},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-51831-1},
url = {https://doi.org/10.1038/s41598-026-51831-1}
}RIS
TY - JOUR TI - Machine learning-based forecasting of rainfall and water demand for urban water planning: the case of Ekurhuleni, South Africa. AU - Lomboli MB AU - Laseinde OT AU - Aigbavboa CO PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-51831-1 UR - https://doi.org/10.1038/s41598-026-51831-1 ER -
APA
MB, L., OT, L., & CO, A. (2026). Machine learning-based forecasting of rainfall and water demand for urban water planning: the case of Ekurhuleni, South Africa.. Scientific reports. https://doi.org/10.1038/s41598-026-51831-1
Source records
- pubmed · retrieved 2026-09-26T20:25:30.113Z