Optimized conditioning factors using machine learning techniques for groundwater potential mapping

• Main Authors: Kalantar, Bahareh, Al-Najjar, Husam A. H., Pradhan, Biswajeet, Saeidi, Vahideh, Abdul Halin, Alfian, Ueda, Naonori, Naghibi, Seyed Amir
• Format: Article
• Language: English
• Published: MDPI 2019
• Online Access: http://psasir.upm.edu.my/id/eprint/38259/1/38259.pdf; http://psasir.upm.edu.my/id/eprint/38259/; https://www.mdpi.com/2073-4441/11/9/1909
• Institution: Universiti Putra Malaysia

Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods—Variance Inflation Factor (VIF), Chi-Square Factor Optimization, and...