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OpenAlex Citation Counts

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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:

Exploring the additional value of class imbalance distributions on interpretable flash flood susceptibility prediction in the Black Warrior River basin, Alabama, United States
Ömer Ekmekcioğlu, Kerim Koç, Mehmet Özger, et al.
Journal of Hydrology (2022) Vol. 610, pp. 127877-127877
Closed Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Predicting and analyzing flood susceptibility using boosting-based ensemble machine learning algorithms with SHapley Additive exPlanations
Halit Enes Aydin, Muzaffer Can İban
Natural Hazards (2022) Vol. 116, Iss. 3, pp. 2957-2991
Closed Access | Times Cited: 86
Explainable artificial intelligence in disaster risk management: Achievements and prospective futures
Saman Ghaffarian, Firouzeh Taghikhah, Holger R. Maier
International Journal of Disaster Risk Reduction (2023) Vol. 98, pp. 104123-104123
Open Access | Times Cited: 57
Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development
Chaitanya B. Pande, Johnbosco C. Egbueri, Romulus Costache, et al.
Journal of Cleaner Production (2024) Vol. 444, pp. 141035-141035
Closed Access | Times Cited: 35
Ensemble learning using multivariate variational mode decomposition based on the Transformer for multi-step-ahead streamflow forecasting
Jinjie Fang, Linshan Yang, Xiaohu Wen, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131275-131275
Closed Access | Times Cited: 17
Flood susceptibility mapping using hybrid models optimized with Artificial Bee Colony
Konstantinos Plataridis, Zisis Mallios
Journal of Hydrology (2023) Vol. 624, pp. 129961-129961
Closed Access | Times Cited: 27
Interpretable machine learning models and decision-making mechanisms for landslide hazard assessment under different rainfall conditions
Haijia Wen, Fangyi Yan, Junhao Huang, et al.
Expert Systems with Applications (2025), pp. 126582-126582
Closed Access | Times Cited: 1
A New Graph-Based Deep Learning Model to Predict Flooding with Validation on a Case Study on the Humber River
Victor Oliveira Santos, Paulo Alexandre Costa Rocha, John Scott, et al.
Water (2023) Vol. 15, Iss. 10, pp. 1827-1827
Open Access | Times Cited: 21
Geographic heterogeneity of activation functions in urban real-time flood forecasting: Based on seasonal trend decomposition using Loess-Temporal Convolutional Network-Gated Recurrent Unit model
Songhua Huan
Journal of Hydrology (2024) Vol. 636, pp. 131279-131279
Closed Access | Times Cited: 6
One-dimensional deep learning driven geospatial analysis for flash flood susceptibility mapping: a case study in North Central Vietnam
Pham Viet Hoa, Nguyễn An Bình, Pham Viet Hong, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 5, pp. 4419-4440
Open Access | Times Cited: 6
Improving the Accuracy of Flood Susceptibility Prediction by Combining Machine Learning Models and the Expanded Flood Inventory Data
Han Yu, Zengliang Luo, Lunche Wang, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3601-3601
Open Access | Times Cited: 14
A Critical Review of Emerging Technologies for Flash Flood Prediction: Examining Artificial Intelligence, Machine Learning, Internet of Things, Cloud Computing, and Robotics Techniques
Ghazi Al-Rawas, Mohammad Reza Nikoo, Malik Al-Wardy, et al.
Water (2024) Vol. 16, Iss. 14, pp. 2069-2069
Open Access | Times Cited: 5
Influencing Factors and Risk Assessment of Precipitation-Induced Flooding in Zhengzhou, China, Based on Random Forest and XGBoost Algorithms
Xun Liu, Peng Zhou, Yi-Chen Lin, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 24, pp. 16544-16544
Open Access | Times Cited: 22
Examining the role of class imbalance handling strategies in predicting earthquake-induced landslide-prone regions
Quoc Bao Pham, Ömer Ekmekcioğlu, Sk Ajim Ali, et al.
Applied Soft Computing (2023) Vol. 143, pp. 110429-110429
Closed Access | Times Cited: 12
Role of National Conditions in Occupational Fatal Accidents in the Construction Industry Using Interpretable Machine Learning Approach
Kerim Koç
Journal of Management in Engineering (2023) Vol. 39, Iss. 6
Closed Access | Times Cited: 11
Urban pluvial flood susceptibility mapping based on a novel explainable machine learning model with synchronous enhancement of fitting capability and explainability
Ze Wang, Heng Lyu, Chi Zhang
Journal of Hydrology (2024) Vol. 642, pp. 131903-131903
Closed Access | Times Cited: 4
Data Uncertainty of Flood Susceptibility Using Non-Flood Samples
Y. Zhang, Yongqiang Wei, Rui Yao, et al.
Remote Sensing (2025) Vol. 17, Iss. 3, pp. 375-375
Open Access
Artificial intelligence and machine learning-powered GIS for proactive disaster resilience in a changing climate
Justin Diehr, Ayorinde Ogunyiola, Oluwabunmi Dada
Annals of GIS (2025), pp. 1-14
Open Access
Flash Flood Regionalization for the Hengduan Mountains Region, China, Combining GNN and SHAP Methods
Yifan Li, Chendi Zhang, Peng Cui, et al.
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 946-946
Open Access
Optimizing flood resilience in China’s mountainous areas: Design flood estimation using advanced machine learning techniques
Xuemei Wang, Ronghua Liu, Chaoxing Sun, et al.
Journal of Hydrology Regional Studies (2025) Vol. 59, pp. 102345-102345
Closed Access
Drought Forecasting Using Integrated Variational Mode Decomposition and Extreme Gradient Boosting
Ömer Ekmekcioğlu
Water (2023) Vol. 15, Iss. 19, pp. 3413-3413
Open Access | Times Cited: 9
Hazard Susceptibility Mapping with Machine and Deep Learning: A Literature Review
Angelly de Jesus Pugliese Viloria, A. Folini, Daniela Carrión, et al.
Remote Sensing (2024) Vol. 16, Iss. 18, pp. 3374-3374
Open Access | Times Cited: 3
Climate change induced disasters and highly vulnerable infrastructure in Uttarakhand, India: current status and way forward towards resilience and long-term sustainability
Gagandeep Singh, Ashish Pandey
Sustainable and Resilient Infrastructure (2023) Vol. 9, Iss. 2, pp. 145-167
Closed Access | Times Cited: 8
Predicting Cost Impacts of Nonconformances in Construction Projects Using Interpretable Machine Learning
Kerim Koç, Cenk Budayan, Ömer Ekmekcioğlu, et al.
Journal of Construction Engineering and Management (2023) Vol. 150, Iss. 1
Closed Access | Times Cited: 7
A Positive-Unlabeled Learning Algorithm for Urban Flood Susceptibility Modeling
Wenkai Li, Yuanchi Liu, Ziyue Liu, et al.
Land (2022) Vol. 11, Iss. 11, pp. 1971-1971
Open Access | Times Cited: 11
Riverine flood potential assessment at municipal level in Slovakia
Matej Vojtek, Saeid Janizadeh, Jana Vojteková
Journal of Hydrology Regional Studies (2022) Vol. 42, pp. 101170-101170
Open Access | Times Cited: 10
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