Groundwater-Potential Mapping Using a Self-Learning Bayesian Network Model: A Comparison among Metaheuristic Algorithms

Groundwater-Potential Mapping Using a Self-Learning Bayesian Network Model: A Comparison among Metaheuristic Algorithms

Owing to the reduction of surface-water resources and frequent droughts, the exploitation of groundwater resources has faced critical challenges. For optimal management of these valuable resources, careful studies of groundwater potential status are essential. The main goal of this study was to dete...

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Bibliographic Details
Main Authors: Sadegh Karimi-Rizvandi, Hamid Valipoori Goodarzi, Javad Hatami Afkoueieh, Il-Moon Chung, Ozgur Kisi, Sungwon Kim, Nguyen Thi Thuy Linh
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Water
Subjects:
groundwater-potential mapping, Bayesian network model, metaheuristic algorithms, geographic information system (GIS), receiver operating characteristic, area under the curve
Online Access:https://www.mdpi.com/2073-4441/13/5/658

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