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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:

Assessing the Benefits of Nature-Inspired Algorithms for the Parameterization of ANN in the Prediction of Water Demand
Salah L. Zubaidi, Nabeel Saleem Saad Al-Bdairi, Sandra Ortega‐Martorell, et al.
Journal of Water Resources Planning and Management (2022) Vol. 149, Iss. 1
Open Access | Times Cited: 11

Showing 11 citing articles:

Improving a hydrological model by coupling it with an LSTM water use forecasting model
Mengqi Wu, Pan Liu, Luguang Liu, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131215-131215
Closed Access | Times Cited: 10
A Hierarchical Hybrid Deep-Net Framework for Water Demand Forecasting Using OPHO Optimization and Deep Learning Techniques
Subha Jeyavelu, K. Aditya Mohan
Iranian Journal of Science and Technology Transactions of Civil Engineering (2025)
Closed Access
Application of Metaheuristic Algorithms and ANN Model for Univariate Water Level Forecasting
Sarah Jasim Mohammed, Salah L. Zubaidi, Nadhir Al‐Ansari, et al.
Advances in Civil Engineering (2023) Vol. 2023, pp. 1-15
Open Access | Times Cited: 9
Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Salah L. Zubaidi, Pavitra Kumar, Hussein Al-Bugharbee, et al.
Applied Water Science (2023) Vol. 13, Iss. 9
Open Access | Times Cited: 5
A Water Demand Forecasting Model Based on Generative Adversarial Networks and Multivariate Feature Fusion
Changchun Yang, Jiayang Meng, Banteng Liu, et al.
Water (2024) Vol. 16, Iss. 12, pp. 1731-1731
Open Access | Times Cited: 1
Metaheuristic algorithms applied in ANN salinity modelling
Zahraa S. Khudhair, Salah L. Zubaidi, Anmar Dulaimi, et al.
Results in Engineering (2024) Vol. 23, pp. 102541-102541
Open Access | Times Cited: 1
Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences
Ziba Zarrin, Omid Hamidi, Payam Amini, et al.
BMC Research Notes (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 1
Examination of Single- and Hybrid-Based Metaheuristic Algorithms in ANN Reference Evapotranspiration Estimating
Hadeel E. Khairan, Salah L. Zubaidi, Syed Fawad Raza, et al.
Sustainability (2023) Vol. 15, Iss. 19, pp. 14222-14222
Open Access | Times Cited: 3
Forecasting urban water demand using different hybrid-based metaheuristic algorithms’ inspire for extracting artificial neural network hyperparameters
Salah L. Zubaidi, Hussein Al-Bugharbee, Ali W. Alattabi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Water Pollution and Water Quality Assessment and Application of Criterion Impact Loss (CILOS), Geographical Information System (GIS), Artificial Neural Network (ANN) and Decision-Learning Technique in River Water Quality Management: An Experiment on the Mahanadi Catchment, Odisha, India
Abhijeet Das
Desalination and Water Treatment (2024), pp. 100969-100969
Open Access
Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
Sarah Jasim Mohammed, Salah L. Zubaidi
Wasit Journal of Engineering Sciences (2023) Vol. 11, Iss. 2, pp. 59-70
Open Access | Times Cited: 1
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