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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:

Two novelty learning models developed based on deep cascade forest to address the environmental imbalanced issues: A case study of drinking water quality prediction
Xingguo Chen, Houtao Liu, Fengrui Liu, et al.
Environmental Pollution (2021) Vol. 291, pp. 118153-118153
Closed Access | Times Cited: 11

Showing 11 citing articles:

Water quality classification using machine learning algorithms
Nida Nasir, Afreen Kansal, Omar Alshaltone, et al.
Journal of Water Process Engineering (2022) Vol. 48, pp. 102920-102920
Closed Access | Times Cited: 201
Spatially adaptive machine learning models for predicting water quality in Hong Kong
Qiaoli Wang, Zijun Li, Jiannan Cai, et al.
Journal of Hydrology (2023) Vol. 622, pp. 129649-129649
Closed Access | Times Cited: 18
Probabilistic machine learning-based phytoplankton abundance using hyperspectral remote sensing
Do Hyuck Kwon, Jung Min Ahn, JongCheol Pyo, et al.
GIScience & Remote Sensing (2025) Vol. 62, Iss. 1
Open Access
Development of entropy-river water quality index for predicting water quality classification through machine learning approach
Deepak Gupta, Virendra Kumar Mishra
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 11, pp. 4249-4271
Closed Access | Times Cited: 10
Online Oil Spill Monitoring Based upon a Shore-Based Hyperspectral Imaging (HIS) System
haixiao qin, Dong Yang, Houxin Cui, et al.
Analytical Letters (2024) Vol. 57, Iss. 18, pp. 3068-3078
Closed Access | Times Cited: 3
Subnetwork prediction approach for aircraft schedule recovery
Imran Haider, Goutam Sen, Mohd Arsalan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108472-108472
Closed Access | Times Cited: 2
A Stacked Ensemble Deep Learning Approach for Imbalanced Multi-Class Water Quality Index Prediction
Wen Yee Wong, Khairunnisa Hasikin‬, Anis Salwa Mohd Khairuddin, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2023) Vol. 76, Iss. 2, pp. 1361-1384
Open Access | Times Cited: 6
Influence of resampling techniques on Bayesian network performance in predicting increased algal activity
Maryam Zeinolabedini, Heather J. Lacey, Lucy Marshall, et al.
Water Research (2023) Vol. 244, pp. 120558-120558
Open Access | Times Cited: 6
A water quality prediction model based on signal decomposition and ensemble deep learning techniques
Jinghan Dong, Zhaocai Wang, Junhao Wu, et al.
Water Science & Technology (2023) Vol. 88, Iss. 10, pp. 2611-2632
Open Access | Times Cited: 4
Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts?
Michael De Santi, Syed Imran Ali, Matthew Arnold, et al.
PLOS Water (2022) Vol. 1, Iss. 9, pp. e0000040-e0000040
Open Access | Times Cited: 4
Prediction of microbiological non-compliances using a Boosted Regression Trees model: application on the drinking water distribution system of a whole country
Mariana Barcia, Alexandra Sixto, María Pía Cerdeiras
Water Science & Technology Water Supply (2024) Vol. 24, Iss. 4, pp. 1080-1088
Open Access
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