Hybrid AI-Geo-informatics framework for river course change prediction and disaster risk mitigation
- DOI
- 10.1038/s41598-026-62726-6
- Published
- 2026-07-21
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-62726-6,
title = {Hybrid AI-Geo-informatics framework for river course change prediction and disaster risk mitigation},
author = {Jay Modhiya and Wasim Khan and Zulfikar Ali Ansari and M. N. V. Kiranbabu and Taher Poonawala and Krishna Dwaipayan Nandi},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-62726-6},
url = {https://doi.org/10.1038/s41598-026-62726-6}
}RIS
TY - JOUR TI - Hybrid AI-Geo-informatics framework for river course change prediction and disaster risk mitigation AU - Jay Modhiya AU - Wasim Khan AU - Zulfikar Ali Ansari AU - M. N. V. Kiranbabu AU - Taher Poonawala AU - Krishna Dwaipayan Nandi PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-62726-6 UR - https://doi.org/10.1038/s41598-026-62726-6 ER -
APA
Modhiya, J., Khan, W., Ansari, Z. A., Kiranbabu, M. N. V., Poonawala, T., & Nandi, K. D. (2026). Hybrid AI-Geo-informatics framework for river course change prediction and disaster risk mitigation. Scientific Reports. https://doi.org/10.1038/s41598-026-62726-6
Source records
- crossref · retrieved 2026-11-06T06:57:54.751Z