Articles | Volume 22, issue 9
https://doi.org/10.5194/hess-22-4771-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-4771-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization
Khabat Khosravi
Department of Watershed Management Engineering, Faculty of Natural
Resources, Sari Agricultural Science and Natural Resources University, Sari,
Iran
Young Researchers and Elites Club, North Tehran Branch, Islamic Azad
University, Tehran, Iran
Dieu Tien Bui
CORRESPONDING AUTHOR
GIS group, Department of Business and IT, University of South-Eastern
Norway, Gullbringvegen 36, 3800 Bø i Telemark, Norway
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133 citations as recorded by crossref.
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- A tree-based intelligence ensemble approach for spatial prediction of potential groundwater M. Avand et al. 10.1080/17538947.2020.1718785
- Comparisons of Diverse Machine Learning Approaches for Wildfire Susceptibility Mapping K. Gholamnia et al. 10.3390/sym12040604
- GIS‐Based Landslide Susceptibility Mapping Using Information, Frequency Ratio, and Artificial Neural Network Methods in Qinghai Province, Northwestern China B. Li et al. 10.1155/2021/4758062
- Mapping groundwater potentiality by using hybrid machine learning models under the scenario of climate variability: a national level study of Bangladesh S. Sarkar et al. 10.1007/s10668-024-04687-2
- Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory T. Gudiyangada Nachappa et al. 10.1016/j.jhydrol.2020.125275
- Multi-Hazard Exposure Mapping Using Machine Learning for the State of Salzburg, Austria T. Nachappa et al. 10.3390/rs12172757
- Integrating Digital Twins and Artificial Intelligence Multi-Modal Transformers into Water Resource Management: Overview and Advanced Predictive Framework T. Syed et al. 10.3390/ai5040098
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Latest update: 25 Dec 2024