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:

Machine learning-based prediction of biological oxygen demand and unit electricity consumption in different-scale wastewater treatment plants
Gang Ye, Jinquan Wan, Zhicheng Deng, et al.
Journal of environmental chemical engineering (2024) Vol. 12, Iss. 2, pp. 111849-111849
Closed Access | Times Cited: 8

Showing 8 citing articles:

AI-driven modelling approaches for predicting oxygen levels in aquatic environments
Rosysmita Bikram Singh, Agnieszka I. Olbert, Avinash Samantra, et al.
Journal of Water Process Engineering (2024) Vol. 66, pp. 105940-105940
Open Access | Times Cited: 10

Enhancing BOD5 Forecasting Accuracy with the ANN-Enhanced Runge Kutta Model
Rana Muhammad Adnan, Ahmed A. Ewees, Mo Wang, et al.
Journal of environmental chemical engineering (2025), pp. 115430-115430
Closed Access

Probabilistic-fuzzy programming model with chance-constrained to optimize wastewater treatment plants: A case study with the Bantul wastewater treatment plant layout
Adiqya May Dwi Armanda, Sutrisno Sutrisno, Sunarsih Sunarsih, et al.
E3S Web of Conferences (2025) Vol. 605, pp. 03036-03036
Open Access

Data-driven prediction of effluent quality in wastewater treatment processes: Model performance optimization and missing-data handling
Zhicheng Deng, Jinquan Wan, Gang Ye, et al.
Journal of Water Process Engineering (2025) Vol. 71, pp. 107352-107352
Closed Access

Dual-stage soft sensor-based fault reconstruction and effluent prediction toward a sustainable wastewater treatment plant using attention fusion deep learning model
Abdulrahman H. Ba-Alawi, Jiyong Kim
Journal of environmental chemical engineering (2025), pp. 116221-116221
Closed Access

Biological oxygen demand prediction using artificial neural network and random forest models enhanced by the neural architecture search algorithm
Amel Fouchal, Yazid Tikhamarine, Mohammed Amin‎ Benbouras, et al.
Modeling Earth Systems and Environment (2024) Vol. 11, Iss. 1
Closed Access | Times Cited: 2

Real-Time Control of A2O Process in Wastewater Treatment Through Fast Deep Reinforcement Learning Based on Data-Driven Simulation Model
Fengyu Hu, Xiaodong Zhang, Baohong Lu, et al.
Water (2024) Vol. 16, Iss. 24, pp. 3710-3710
Open Access | Times Cited: 1

Hybrid modeling techniques for predicting chemical oxygen demand in wastewater treatment: a stacking ensemble learning approach with neural networks
S Ramya, S Srinath, Pushpa Tuppad
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 12
Closed Access

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