K-Fold and State-of-the-Art Metaheuristic Machine Learning Approaches for Groundwater Potential Modelling

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Detalles Bibliográficos
Publicado en:	Water Resources Management vol. 35, no. 6 (Apr 2021), p. 1837
Autor principal:	Arabameri Alireza
Otros Autores:	Arora Aman, Pal, Subodh Chandra, Mitra Satarupa, Saha Asish, Asadi, Nalivan Omid, Panahi Somayeh, Moayedi Hossein
Publicado:	Springer Nature B.V.
Materias:	Geology Groundwater potential Maps Rainfall Fuzzy logic Artificial neural networks Lithology Drainage density Machine learning Zonation Groundwater Learning algorithms Heuristic methods Model accuracy Adaptive systems Specificity Hydrogeology Accuracy Distance Collinearity Fireflies Rain Environmental
Acceso en línea:	Citation/Abstract Full Text - PDF
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