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:

IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling
Babak Mohammadi, Mir Jafar Sadegh Safari, Saeed Vazifehkhah
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

A novel hybrid BPNN model based on adaptive evolutionary Artificial Bee Colony Algorithm for water quality index prediction
Lingxuan Chen, Tunhua Wu, Zhaocai Wang, et al.
Ecological Indicators (2023) Vol. 146, pp. 109882-109882
Open Access | Times Cited: 109

DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling
Arpit Kapoor, Sahani Pathiraja, Lucy Marshall, et al.
Environmental Modelling & Software (2023) Vol. 169, pp. 105831-105831
Open Access | Times Cited: 42

Optimization of high-performance concrete mix ratio design using machine learning
Bin Chen, Lei Wang, Zongbao Feng, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 122, pp. 106047-106047
Closed Access | Times Cited: 32

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: 23

Novel hybrid intelligence predictive model based on successive variational mode decomposition algorithm for monthly runoff series
Abbas Parsaie, Redvan Ghasemlounıa, Amin Gharehbaghi, et al.
Journal of Hydrology (2024) Vol. 634, pp. 131041-131041
Closed Access | Times Cited: 13

Enhancing Streamflow Prediction Physically Consistently Using Process-Based Modeling and Domain Knowledge: A Review
Bisrat Ayalew Yifru, Kyoung Jae Lim, Seoro Lee
Sustainability (2024) Vol. 16, Iss. 4, pp. 1376-1376
Open Access | Times Cited: 9

Predicting solar distiller productivity using an AI Approach: Modified genetic algorithm with Multi-Layer Perceptron
Eman Ashraf, A.E. Kabeel, Yehia Elmashad, et al.
Solar Energy (2023) Vol. 263, pp. 111964-111964
Closed Access | Times Cited: 16

Application of novel artificial bee colony optimized ANN and data preprocessing techniques for monthly streamflow estimation
Okan Mert Katipoğlu, Mehdi Keblouti, Babak Mohammadi
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 38, pp. 89705-89725
Closed Access | Times Cited: 15

Application of hybrid machine learning-based ensemble techniques for rainfall-runoff modeling
Gebre Gelete
Earth Science Informatics (2023) Vol. 16, Iss. 3, pp. 2475-2495
Closed Access | Times Cited: 15

Comparison and integration of physical and interpretable AI-driven models for rainfall-runoff simulation
Sara Asadi, Patricia Jimeno‐Sáez, Adrián López-Ballesteros, et al.
Results in Engineering (2024) Vol. 24, pp. 103048-103048
Open Access | Times Cited: 5

Advancements in rainfall-runoff prediction: Exploring state-of-the-art neural computing modeling approaches
Dani Irwan, Ali Najah Ahmed, Saerahany Legori Ibrahim, et al.
Alexandria Engineering Journal (2025) Vol. 121, pp. 138-149
Closed Access

Integration of Gaussian process regression and K means clustering for enhanced short term rainfall runoff modeling
Özgür Kişi, Salim Heddam, Kulwinder Singh Parmar, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access

Reference evapotranspiration estimation in hyper-arid regions via D-vine copula based-quantile regression and comparison with empirical approaches and machine learning models
Mohammed Abdallah, Babak Mohammadi, Modathir Zaroug, et al.
Journal of Hydrology Regional Studies (2022) Vol. 44, pp. 101259-101259
Open Access | Times Cited: 26

Rainfall-Runoff Simulation in Ungauged Tributary Streams Using Drainage Area Ratio-Based Multivariate Adaptive Regression Spline and Random Forest Hybrid Models
Babak Vaheddoost, Mir Jafar Sadegh Safari, Mustafa Utku Yılmaz
Pure and Applied Geophysics (2023) Vol. 180, Iss. 1, pp. 365-382
Closed Access | Times Cited: 13

The projected futures of water resources vulnerability under climate and socioeconomic change in the Yangtze River Basin, China
Xiu Zhang, Yuqing Tian, Na Dong, et al.
Ecological Indicators (2023) Vol. 147, pp. 109933-109933
Open Access | Times Cited: 13

Streamflow Simulation in Semiarid Data-Scarce Regions: A Comparative Study of Distributed and Lumped Models at Aguenza Watershed (Morocco)
Abdelmounim Bouadila, Ismail Bouizrou, Mourad Aqnouy, et al.
Water (2023) Vol. 15, Iss. 8, pp. 1602-1602
Open Access | Times Cited: 10

Efficiency of global precipitation datasets in tropical and subtropical catchments revealed by large sampling hydrological modelling
João Andrade, Alfredo Ribeiro Neto, Rodolfo Nóbrega, et al.
Journal of Hydrology (2024) Vol. 633, pp. 131016-131016
Open Access | Times Cited: 3

Study on land use conflict identification and territorial spatial zoning control in Rao River Basin, Jiangxi Province, China
Liting Chen, Haisheng Cai
Ecological Indicators (2022) Vol. 145, pp. 109594-109594
Closed Access | Times Cited: 16

Physical and artificial intelligence-based hybrid models for rainfall–runoff–sediment process modelling
Gebre Gelete, Vahid Nourani, Hüseyin Gökçekuş, et al.
Hydrological Sciences Journal (2023) Vol. 68, Iss. 13, pp. 1841-1863
Closed Access | Times Cited: 9

Enhancing Rainfall-Runoff Simulation via Meteorological Variables and a Deep-Conceptual Learning-Based Framework
Mohammed Achite, Babak Mohammadi, Muhammad Jehanzaib, et al.
Atmosphere (2022) Vol. 13, Iss. 10, pp. 1688-1688
Open Access | Times Cited: 14

A hybrid rainfall-runoff model: integrating initial loss and LSTM for improved forecasting
Wei Wang, Jie Gao, Zheng Liu, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 8

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