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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:

Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms
Khabat Khosravi, Ali Golkarian, John P. Tiefenbacher
Water Resources Management (2022) Vol. 36, Iss. 2, pp. 699-716
Closed Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management
Vijendra Kumar, Hazi Mohammad Azamathulla, Kul Vaibhav Sharma, et al.
Sustainability (2023) Vol. 15, Iss. 13, pp. 10543-10543
Open Access | Times Cited: 99
A review of hybrid deep learning applications for streamflow forecasting
Kin‐Wang Ng, Yuk Feng Huang, Chai Hoon Koo, et al.
Journal of Hydrology (2023) Vol. 625, pp. 130141-130141
Closed Access | Times Cited: 77
Application of Machine Learning in Water Resources Management: A Systematic Literature Review
Fatemeh Ghobadi, Doosun Kang
Water (2023) Vol. 15, Iss. 4, pp. 620-620
Open Access | Times Cited: 73
Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling
Keighobad Jafarzadegan, Hamid Moradkhani, Florian Pappenberger, et al.
Reviews of Geophysics (2023) Vol. 61, Iss. 2
Open Access | Times Cited: 67
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao Hai, Sani I. Abba, Ahmed M. Al‐Areeq, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107559-107559
Closed Access | Times Cited: 58
Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft computing techniques
Charuni I. Madhushani, K. G. S. Dananjaya, I.U. Ekanayake, et al.
Journal of Hydrology (2024) Vol. 631, pp. 130846-130846
Closed Access | Times Cited: 23
Daily River flow Simulation Using Ensemble Disjoint Aggregating M5-Prime Model
Khabat Khosravi, Nasrin Fathollahzadeh Attar, Sayed M. Bateni, et al.
Heliyon (2024) Vol. 10, Iss. 20, pp. e37965-e37965
Open Access | Times Cited: 17
Pre- and post-dam river water temperature alteration prediction using advanced machine learning models
Dinesh Kumar Vishwakarma, Rawshan Ali, Shakeel Ahmad Bhat, et al.
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 55, pp. 83321-83346
Open Access | Times Cited: 41
Application of Innovative Machine Learning Techniques for Long-Term Rainfall Prediction
Suman Markuna, Pankaj Kumar, Rawshan Ali, et al.
Pure and Applied Geophysics (2023) Vol. 180, Iss. 1, pp. 335-363
Closed Access | Times Cited: 33
A Novel Smoothing-Based Deep Learning Time-Series Approach for Daily Suspended Sediment Load Prediction
Bibhuti Bhusan Sahoo, Sovan Sankalp, Özgür Kişi
Water Resources Management (2023) Vol. 37, Iss. 11, pp. 4271-4292
Closed Access | Times Cited: 25
A conceptual metaheuristic-based framework for improving runoff time series simulation in glacierized catchments
Babak Mohammadi, Saeed Vazifehkhah, Zheng Duan
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107302-107302
Open Access | Times Cited: 24
Coupling machine learning and physical modelling for predicting runoff at catchment scale
Sergio Zubelzu, Abdulmomen Ghalkha, Chaouki Ben Issaid, et al.
Journal of Environmental Management (2024) Vol. 354, pp. 120404-120404
Open Access | Times Cited: 6
Enhancing Flood Risk Mitigation by Advanced Data-Driven Approach
Ali S. Chafjiri, Mohammad Gheibi, Benyamin Chahkandi, et al.
Heliyon (2024) Vol. 10, Iss. 18, pp. e37758-e37758
Open Access | Times Cited: 6
Enhanced monthly streamflow prediction using an input–output bi-decomposition data driven model considering meteorological and climate information
Qiucen Guo, Xuehua Zhao, Yuhang Zhao, et al.
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 8, pp. 3059-3077
Closed Access | Times Cited: 5
Deep learning algorithms and their fuzzy extensions for streamflow prediction in climate change framework
Rishith Kumar Vogeti, Rahul Jauhari, Bhavesh Rahul Mishra, et al.
Journal of Water and Climate Change (2024) Vol. 15, Iss. 2, pp. 832-848
Open Access | Times Cited: 5
Streamflow prediction using support vector regression machine learning model for Tehri Dam
Bhanu Sharma, N. K. Goel
Applied Water Science (2024) Vol. 14, Iss. 5
Open Access | Times Cited: 5
Improving medium-range streamflow forecasts over South Korea with a dual-encoder transformer model
Dong-Gi Lee, Kuk‐Hyun Ahn
Journal of Environmental Management (2024) Vol. 368, pp. 122114-122114
Closed Access | Times Cited: 4
Advanced Soft Computing Techniques for Monthly Streamflow Prediction in Seasonal Rivers
Mohammed Achite, Okan Mert Katipoğlu, Veysi Kartal, et al.
Atmosphere (2025) Vol. 16, Iss. 1, pp. 106-106
Open Access
Multi-Step Ahead Probabilistic Forecasting of Daily Streamflow Using Bayesian Deep Learning: A Multiple Case Study
Fatemeh Ghobadi, Doosun Kang
Water (2022) Vol. 14, Iss. 22, pp. 3672-3672
Open Access | Times Cited: 19
Improving the interpretability and predictive power of hydrological models: Applications for daily streamflow in managed and unmanaged catchments
Pravin Bhasme, Udit Bhatia
Journal of Hydrology (2023) Vol. 628, pp. 130421-130421
Closed Access | Times Cited: 11
A Hybrid ANFIS-GA Approach for Estimation of Hydrological Time Series
Bülent Haznedar, Hüseyin Çağan Kılınç
Water Resources Management (2022) Vol. 36, Iss. 12, pp. 4819-4842
Closed Access | Times Cited: 17
Short-term streamflow modeling using data-intelligence evolutionary machine learning models
Alfeu D. Martinho, Henrique S. Hippert, Leonardo Goliatt
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 10
Monthly streamflow prediction and performance comparison of machine learning and deep learning methods
Ömer Ayana, Deniz Furkan Kanbak, Mümine Kaya Keleş, et al.
Acta Geophysica (2023) Vol. 71, Iss. 6, pp. 2905-2922
Closed Access | Times Cited: 9
A Comparative Analysis of Multiple Machine Learning Methods for Flood Routing in the Yangtze River
Liwei Zhou, Ling Kang
Water (2023) Vol. 15, Iss. 8, pp. 1556-1556
Open Access | Times Cited: 9
A Convolutional Neural Network-Based Feature Extraction and Weighted Twin Support Vector Machine Algorithm for Context-Aware Human Activity Recognition
Kwok Tai Chui, Brij B. Gupta, Miguel Torres-Ruiz, et al.
Electronics (2023) Vol. 12, Iss. 8, pp. 1915-1915
Open Access | Times Cited: 9
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