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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Hybrid computational intelligence models for groundwater potential mapping
Binh Thai Pham, Abolfazl Jaafari, Indra Prakash, et al.
CATENA (2019) Vol. 182, pp. 104101-104101
Closed Access | Times Cited: 130

Showing 1-25 of 130 citing articles:

A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
Dong Van Dao, Abolfazl Jaafari, Mahmoud Bayat, et al.
CATENA (2020) Vol. 188, pp. 104451-104451
Closed Access | Times Cited: 292
Groundwater level prediction using machine learning models: A comprehensive review
Tao Hai, Mohammed Majeed Hameed, Haydar Abdulameer Marhoon, et al.
Neurocomputing (2022) Vol. 489, pp. 271-308
Open Access | Times Cited: 265
Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran
Saeid Janizadeh, Mohammadtaghi Avand, Abolfazl Jaafari, et al.
Sustainability (2019) Vol. 11, Iss. 19, pp. 5426-5426
Open Access | Times Cited: 234
Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction
Binh Thai Pham, Abolfazl Jaafari, Mohammadtaghi Avand, et al.
Symmetry (2020) Vol. 12, Iss. 6, pp. 1022-1022
Open Access | Times Cited: 231
GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment
Binh Thai Pham, Mohammadtaghi Avand, Saeid Janizadeh, et al.
Water (2020) Vol. 12, Iss. 3, pp. 683-683
Open Access | Times Cited: 207
Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential Mapping
Phong Tung Nguyen, Duong Hai Ha, Mohammadtaghi Avand, et al.
Applied Sciences (2020) Vol. 10, Iss. 7, pp. 2469-2469
Open Access | Times Cited: 155
Flood risk assessment using deep learning integrated with multi-criteria decision analysis
Binh Thai Pham, Chinh Luu, Dong Van Dao, et al.
Knowledge-Based Systems (2021) Vol. 219, pp. 106899-106899
Closed Access | Times Cited: 115
Critical role of climate factors for groundwater potential mapping in arid regions: Insights from random forest, XGBoost, and LightGBM algorithms
Xu Guo, Xiaofan Gui, Hanxiang Xiong, et al.
Journal of Hydrology (2023) Vol. 621, pp. 129599-129599
Closed Access | Times Cited: 80
GIS-based machine learning algorithm for flood susceptibility analysis in the Pagla river basin, Eastern India
Nur Islam Saikh, Prolay Mondal
Natural Hazards Research (2023) Vol. 3, Iss. 3, pp. 420-436
Open Access | Times Cited: 47
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
Binh Thai Pham, T. Nguyen‐Thoi, Chongchong Qi, et al.
CATENA (2020) Vol. 195, pp. 104805-104805
Closed Access | Times Cited: 136
Groundwater Potential Mapping Using Remote Sensing and GIS-Based Machine Learning Techniques
Sunmin Lee, Yunjung Hyun, Saro Lee, et al.
Remote Sensing (2020) Vol. 12, Iss. 7, pp. 1200-1200
Open Access | Times Cited: 128
Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam
Phong Tung Nguyen, Duong Hai Ha, Abolfazl Jaafari, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 7, pp. 2473-2473
Open Access | Times Cited: 125
Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
Viet‐Ha Nhu, Ayub Mohammadi, Himan Shahabi, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 14, pp. 4933-4933
Open Access | Times Cited: 121
Deep learning neural networks for spatially explicit prediction of flash flood probability
Mahdi Panahi, Abolfazl Jaafari, Ataollah Shirzadi, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101076-101076
Open Access | Times Cited: 120
Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran
Viet‐Ha Nhu, Ataollah Shirzadi, Himan Shahabi, et al.
Forests (2020) Vol. 11, Iss. 4, pp. 421-421
Open Access | Times Cited: 115
Application of extreme gradient boosting and parallel random forest algorithms for assessing groundwater spring potential using DEM-derived factors
Seyed Amir Naghibi, Hossein Hashemi, Ronny Berndtsson, et al.
Journal of Hydrology (2020) Vol. 589, pp. 125197-125197
Closed Access | Times Cited: 112
A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping
Binh Thai Pham, Tran Van Phong, Huu Duy Nguyen, et al.
Water (2020) Vol. 12, Iss. 1, pp. 239-239
Open Access | Times Cited: 111
Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh
Swades Pal, Sonali Kundu, Susanta Mahato
Journal of Cleaner Production (2020) Vol. 257, pp. 120311-120311
Closed Access | Times Cited: 108
Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques
Haitham Abdulmohsin Afan, Ahmedbahaaaldin Ibrahem Ahmed Osman, Yusuf Essam, et al.
Engineering Applications of Computational Fluid Mechanics (2021) Vol. 15, Iss. 1, pp. 1420-1439
Open Access | Times Cited: 104
DEM resolution effects on machine learning performance for flood probability mapping
Mohammadtaghi Avand, Alban Kuriqi, Majid Khazaei, et al.
Journal of Hydro-environment Research (2021) Vol. 40, pp. 1-16
Open Access | Times Cited: 104
GIS-Based Gully Erosion Susceptibility Mapping: A Comparison of Computational Ensemble Data Mining Models
Viet‐Ha Nhu, Saeid Janizadeh, Mohammadtaghi Avand, et al.
Applied Sciences (2020) Vol. 10, Iss. 6, pp. 2039-2039
Open Access | Times Cited: 98
A Gene Expression Programming Model for Predicting Tunnel Convergence
Mohsen Hajihassani, Shahrum Shah Abdullah, Panagiotis G. Asteris, et al.
Applied Sciences (2019) Vol. 9, Iss. 21, pp. 4650-4650
Open Access | Times Cited: 97
Modeling groundwater potential using novel GIS-based machine-learning ensemble techniques
Alireza Arabameri, Subodh Chandra Pal, Fatemeh Rezaie, et al.
Journal of Hydrology Regional Studies (2021) Vol. 36, pp. 100848-100848
Open Access | Times Cited: 97
Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques
Binh Thai Pham, Abolfazl Jaafari, Tran Van Phong, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101105-101105
Open Access | Times Cited: 95
A tree-based intelligence ensemble approach for spatial prediction of potential groundwater
Mohammadtaghi Avand, Saeid Janizadeh, Dieu Tien Bui, et al.
International Journal of Digital Earth (2020) Vol. 13, Iss. 12, pp. 1408-1429
Closed Access | Times Cited: 94
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