Assessing the performance of machine learning and analytical hierarchy process (AHP) models for rainwater harvesting potential zone identification in hilly region, Bangladesh

Assessing the performance of machine learning and analytical hierarchy process (AHP) models for rainwater harvesting potential zone identification in hilly region, Bangladesh

Water scarcity in hilly regions presents unique challenges, particularly in Bangladesh, where obtaining fresh drinking water has become difficult to access. This study aims to evaluate the potential zones for rainwater harvesting (RWH) using machine learning (ML) algorithms and geospatial analysis....

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Hlavní autoři: Md. Mahmudul Hasan, Md. Talha, Most. Mitu Akter, Md Tasim Ferdous, Pratik Mojumder, Sujit Kumar Roy, N.M. Refat Nasher
Médium: Článek
Jazyk:English
Vydáno: Elsevier 2025-06-01
Edice:Journal of Asian Earth Sciences: X
Témata:
Rainwater harvesting
Hill tracts
Machine learning (ML)
Analytical hierarchy process (AHP)
Chattogram
On-line přístup:http://www.sciencedirect.com/science/article/pii/S2590056024000173

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http://www.sciencedirect.com/science/article/pii/S2590056024000173

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