Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Deep Learning and Machine Learning in Hydrological Processes Climate Change and Earth Systems a Systematic Review
Sina Ardabili, Amir Mosavi, Majid Dehghani, et al.
Lecture notes in networks and systems (2020), pp. 52-62
Closed Access | Times Cited: 132

Showing 1-25 of 132 citing articles:

Artificial Neural Networks Based Optimization Techniques: A Review
Maher G. M. Abdolrasol, S. M. Suhail Hussain, Taha Selim Ustun, et al.
Electronics (2021) Vol. 10, Iss. 21, pp. 2689-2689
Open Access | Times Cited: 427
A comprehensive review of deep learning applications in hydrology and water resources
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang, et al.
Water Science & Technology (2020) Vol. 82, Iss. 12, pp. 2635-2670
Open Access | Times Cited: 403
COVID-19 Outbreak Prediction with Machine Learning
Sina Ardabili, Amir Mosavi, Pedram Ghamisi, et al.
Algorithms (2020) Vol. 13, Iss. 10, pp. 249-249
Open Access | Times Cited: 321
COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach
Gergő Pintér, Imre Felde, Amir Mosavi, et al.
Mathematics (2020) Vol. 8, Iss. 6, pp. 890-890
Open Access | Times Cited: 230
Advances in Machine Learning Modeling Reviewing Hybrid and Ensemble Methods
Sina Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy
Lecture notes in networks and systems (2020), pp. 215-227
Closed Access | Times Cited: 171
Estimation of daily maize transpiration using support vector machines, extreme gradient boosting, artificial and deep neural networks models
Junliang Fan, Jing Zheng, Lifeng Wu, et al.
Agricultural Water Management (2020) Vol. 245, pp. 106547-106547
Closed Access | Times Cited: 170
A novel intelligent deep learning predictive model for meteorological drought forecasting
Ali Danandeh Mehr, Amir Rikhtehgar Ghiasi, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, et al.
Journal of Ambient Intelligence and Humanized Computing (2022) Vol. 14, Iss. 8, pp. 10441-10455
Closed Access | Times Cited: 143
Comparison of Deep Learning Techniques for River Streamflow Forecasting
Xuan-Hien Le, Duc Hai Nguyen, Sungho Jung, et al.
IEEE Access (2021) Vol. 9, pp. 71805-71820
Open Access | Times Cited: 117
Integrating Machine Learning and AI for Improved Hydrological Modeling and Water Resource Management
Djabeur Mohamed Seifeddine Zekrifa, Megha Kulkarni, A. Bhagyalakshmi, et al.
Advances in environmental engineering and green technologies book series (2023), pp. 46-70
Closed Access | Times Cited: 64
A critical review of machine learning algorithms in maritime, offshore, and oil & gas corrosion research: A comprehensive analysis of ANN and RF models
Md Mahadi Hasan Imran, Shahrizan Jamaludin, Ahmad Faisal Mohamad Ayob
Ocean Engineering (2024) Vol. 295, pp. 116796-116796
Closed Access | Times Cited: 24
Article Context and Technological Integration: AI's Role in Climate Change Research
Fredrick Kayusi, Srinivas Kasulla, S J Malik, et al.
LatIA (2025) Vol. 3, pp. 85-85
Closed Access | Times Cited: 2
Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
Shahab S. Band, Mahdis Fathi, Anthony T. Chronopoulos, et al.
Journal of Information Security and Applications (2020) Vol. 55, pp. 102582-102582
Closed Access | Times Cited: 119
Statistical downscaling of daily temperature and precipitation over China using deep learning neural models: Localization and comparison with other methods
Lei Sun, Yufeng Lan
International Journal of Climatology (2020) Vol. 41, Iss. 2, pp. 1128-1147
Closed Access | Times Cited: 97
Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information
Mojtaba Sadeghi, Phu Nguyen, Kuolin Hsu, et al.
Environmental Modelling & Software (2020) Vol. 134, pp. 104856-104856
Open Access | Times Cited: 93
Systematic Review of Deep Learning and Machine Learning Models in Biofuels Research
Sina Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy
Lecture notes in networks and systems (2020), pp. 19-32
Closed Access | Times Cited: 91
Groundwater quality evaluation using hybrid model of the multi-layer perceptron combined with neural-evolutionary regression techniques: case study of Shiraz plain
Hossein Moayedi, Marjan Salari, Atefeh Ahmadi Dehrashid, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 8, pp. 2961-2976
Closed Access | Times Cited: 30
Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review
Sancho Salcedo‐Sanz, Jorge Pérez‐Aracil, Guido Ascenso, et al.
Theoretical and Applied Climatology (2023) Vol. 155, Iss. 1, pp. 1-44
Open Access | Times Cited: 30
A New Benchmark on Machine Learning Methodologies for Hydrological Processes Modelling: A Comprehensive Review for Limitations and Future Research Directions
Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
Knowledge-Based Engineering and Sciences (2023) Vol. 4, Iss. 3, pp. 65-103
Open Access | Times Cited: 25
Green intelligence: the AI content of green technologies
Gianluca Biggi, Martina Iori, Julia Mazzei, et al.
Eurasian Economic Review (2025)
Open Access | Times Cited: 1
Enhancing Wetland Restoration through Machine Learning-Based Decision Support Systems
Fredrick Kayusi, Petros Chavula
LatIA (2025) Vol. 3, pp. 81-81
Closed Access | Times Cited: 1
List of Deep Learning Models
Amir Mosavi, Sina Ardabili, Annamária R. Várkonyi-Kóczy
Lecture notes in networks and systems (2020), pp. 202-214
Closed Access | Times Cited: 66
COVID-19 Pandemic Prediction for Hungary; a Hybrid Machine Learning Approach
Gergő Pintér, Imre Felde, Amir Mosavi, et al.
Research Square (Research Square) (2020)
Open Access | Times Cited: 64
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang, et al.
EarthArXiv (California Digital Library) (2020)
Open Access | Times Cited: 56
Separating the Impacts of Climate Change and Human Activities on Runoff: A Review of Method and Application
F. J. Zeng, Mingguo Ma, Dongrui Di, et al.
Water (2020) Vol. 12, Iss. 8, pp. 2201-2201
Open Access | Times Cited: 56
Page 1 - Next Page

Scroll to top