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:

Water footprint modeling and forecasting of cassava based on different artificial intelligence algorithms in Guangxi, China
Mingfeng Tao, Tingting Zhang, Xiaomin Xie, et al.
Journal of Cleaner Production (2022) Vol. 382, pp. 135238-135238
Closed Access | Times Cited: 14

Showing 14 citing articles:

A multi-model data fusion methodology for reservoir water quality based on machine learning algorithms and bayesian maximum entropy
Mohammad Zamani, Mohammad Reza Nikoo, Fereshteh Niknazar, et al.
Journal of Cleaner Production (2023) Vol. 416, pp. 137885-137885
Closed Access | Times Cited: 34

Artificial Intelligence for Water Consumption Assessment: State of the Art Review
Almando Morain, Nivedita Ilangovan, Christopher Delhom, et al.
Water Resources Management (2024) Vol. 38, Iss. 9, pp. 3113-3134
Open Access | Times Cited: 5

Cutting-Edge Technologies: Biofuel Innovations in Marine Propulsion Systems to lower black carbon emissions
S. Manikandan, Sundaram Vickram, Yuvarajan Devarajan
Results in Engineering (2025), pp. 104095-104095
Open Access

Water Conservation
P. Selvakumar, M. S. Usha, Sonali R. Dhokpande, et al.
Advances in environmental engineering and green technologies book series (2025), pp. 269-296
Closed Access

AI Applications in Drinking-Water Management
P. Selvakumar, R. V. N. Srivastava, Sumanta Bhattacharya, et al.
IGI Global eBooks (2025), pp. 307-336
Closed Access

Medium-term water consumption forecasting based on deep neural networks
Adrián Gil Gamboa, Pilar Paneque, Óscar Trull, et al.
Expert Systems with Applications (2024) Vol. 247, pp. 123234-123234
Open Access | Times Cited: 4

Bioenergy relations with agriculture, forestry and other land uses: Highlighting the specific contributions of artificial intelligence and co-citation networks
Vítor João Pereira Domingues Martinho, Raimundo Nonato Rodrigues
Heliyon (2024) Vol. 10, Iss. 4, pp. e26267-e26267
Open Access | Times Cited: 4

Effluent parameters prediction of a biological nutrient removal (BNR) process using different machine learning methods: A case study
Neslihan Manav Demır, Huseyin Baran Gelgor, Ersoy Öz, et al.
Journal of Environmental Management (2023) Vol. 351, pp. 119899-119899
Closed Access | Times Cited: 9

Leveraging Deep Learning and Language Models in Revolutionizing Water Resource Management, Research, and Policy Making: A Case for ChatGPT
Partha Pratim Ray
ACS ES&T Water (2023) Vol. 3, Iss. 8, pp. 1984-1986
Closed Access | Times Cited: 8

Unlocking the potential: A review of artificial intelligence applications in wind energy
Safa Dörterler, Seyfullah Arslan, Durmuş Özdemir
Expert Systems (2024) Vol. 41, Iss. 12
Open Access | Times Cited: 2

A Detailed Examination of China’s Clean Energy Mineral Consumption: Footprints, Trends, and Drivers
Chuandi Fang, Jinhua Cheng, Zhe You, et al.
Sustainability (2023) Vol. 15, Iss. 23, pp. 16255-16255
Open Access | Times Cited: 2

Machine Learning Insights into Türkiye’s Climate Variability: Predictive Modelling and Spatial Analysis
Taha Yasin Hatay, Bülent Turgut, Şahin Işık, et al.
Authorea (Authorea) (2024)
Open Access

Estimating virtual water content and yield of wheat using machine learning tools
Abdullah Muratoğlu, Muhammed Sungur Demir, Mete Yaganoglu, et al.
Journal of Hydrology (2024), pp. 132526-132526
Closed Access

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