Optimized Conditioning Factors Using Machine Learning Techniques for Groundwater Potential Mapping

Optimized Conditioning Factors Using Machine Learning Techniques for Groundwater Potential Mapping

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 Optimiz...

Full description

Bibliographic Details
Main Authors: Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda, Seyed Amir Naghibi
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Water
Subjects:
springs potential mapping
mixture discriminant analysis
GIS
random forest
linear discriminant analysis
Online Access:https://www.mdpi.com/2073-4441/11/9/1909

Internet

https://www.mdpi.com/2073-4441/11/9/1909

Similar Items