water Article A Hybrid Computational Intelligence Approach to Groundwater Spring Potential Mapping Dieu Tien Bui 1,2, Ataollah Shirzadi 3 , Kamran Chapi 3 , Himan Shahabi 4 , Biswajeet Pradhan 5,6 , Binh Thai Pham 7,* , Vijay P. Singh 8, Wei Chen 9, Khabat Khosravi 10 , Baharin Bin Ahmad 11 and Saro Lee 12,13,* 1 Geographic Information Science Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam;
[email protected] 2 Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam 3 Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj 66177-15175, Iran;
[email protected] (A.S.);
[email protected] (K.C.) 4 Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Sanandaj 66177-15175, Iran;
[email protected] 5 Center for Advanced Modeling and Geospatial System (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, CB11.06.106, Building 11, 81 Broadway, Sydney, NSW 2007, Australia;
[email protected] 6 Department of Energy and Mineral Resources Engineering, Sejong University, Choongmu-gwan, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea 7 Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam 8 Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843-2117, USA;
[email protected] 9 College of Geology and Environment, Xi’an University of Science and Technology,