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Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm |
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| Authors: | Mohamadi Sedigheh Sammen Saad Sh Panahi Fatemeh Ehteram Mohammad Kisi Ozgur Mosavi Amir Ahmed Ali Najah El-Shafie Ahmed Al-Ansari Nadhir |
| Institution: | 1.Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran ;2.Department of Civil Engineering, College of Engineering, University of Diyala, Baqubah, Diyala Governorate, Iraq ;3.Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran ;4.Department of Water Engineering and Hydraulic Structures, Faculty of Civil Engineering, Semnan University, Semnan, Iran ;5.Department of Civil Engineering, School of Technology, IIia State University, 0162, Tbilisi, Georgia ;6.Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam ;7.Environmental Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam ;8.Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam ;9.Institute of Energy Infrastructure (IEI), Universiti Tenaga Nasional (UNITEN), 43000, Kajang, Selangor Darul Ehsan, Malaysia ;10.Department of Civil Engineering, Faculty of Engineering, University of Malaya (UM), 50603, Kuala Lumpur, Malaysia ;11.National Water Center (NWC), United Arab Emirates University, P.O. Box 15551, Al Ain, UAE ;12.Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 97187, Lule?, Sweden ; |
| Abstract: | Natural Hazards - The modelling of drought is of utmost importance for the efficient management of water resources. This article used the adaptive neuro-fuzzy interface system (ANFIS), multilayer... |
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