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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:

Using Machine Learning Methods to Forecast Air Quality: A Case Study in Macao
Thomas M. T. Lei, Shirley W. I. Siu, Joana Monjardino, et al.
Atmosphere (2022) Vol. 13, Iss. 9, pp. 1412-1412
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Application of ANN, XGBoost, and Other ML Methods to Forecast Air Quality in Macau
Thomas M. T. Lei, Stanley C. W. Ng, Shirley W. I. Siu
Sustainability (2023) Vol. 15, Iss. 6, pp. 5341-5341
Open Access | Times Cited: 34
Prediction of wastewater treatment plant performance through machine learning techniques
Hani Mahanna, Nora El-Rashidy, Mosbeh R. Kaloop, et al.
Desalination and Water Treatment (2024) Vol. 319, pp. 100524-100524
Open Access | Times Cited: 10
AI-driven approaches for air pollution modeling: A comprehensive systematic review
Lorenzo Garbagna, Lakshmi Babu Saheer, Mahdi Maktabdar Oghaz
Environmental Pollution (2025), pp. 125937-125937
Closed Access | Times Cited: 1
Spatio-temporal visualization and forecasting of $${\text {PM}}_{10}$$ in the Brazilian state of Minas Gerais
Kim Leone Souza da Silva, Javier Linkolk López‐Gonzales, Josue E. Turpo-Chaparro, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon
Vitrice Ruben Folifack Signing, Jacob Mbarndouka Taamté, Michaux Kountchou, et al.
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 7
Closed Access | Times Cited: 5
Air Quality Prediction Using Machine Learning Techniques
Rajeev Kumar Mishra, Rahul Rana, Satya Prakash Singh Tomar, et al.
(2025), pp. 305-320
Closed Access
Assessing the Impact of a Low-Emission Zone on Air Quality Using Machine Learning Algorithms in a Business-As-Usual Scenario
Marta Doval Miñarro, María C. Bueso, Pedro Antonio Guillén-Alcaraz
Sustainability (2025) Vol. 17, Iss. 8, pp. 3582-3582
Open Access
Study of the Dynamical Relationships between PM2.5 and PM10 in the Caribbean Area Using a Multiscale Framework
Thomas Plocoste, S. Adarsh, Lovely Euphrasie-Clotilde
Atmosphere (2023) Vol. 14, Iss. 3, pp. 468-468
Open Access | Times Cited: 10
Comparative Analysis of Machine Learning Models for Predicting PM2.5 Concentrations Using Meteorological and Chemical Indicators
Muhammad Haseeb, Zainab Tahir, Syed Amer Mahmood, et al.
Journal of Atmospheric and Solar-Terrestrial Physics (2024) Vol. 263, pp. 106338-106338
Closed Access | Times Cited: 3
A Novel Hybrid Prediction Model of Air Quality Index Based on Variational Modal Decomposition and CEEMDAN-SE-GRU
Chaoli Tang, Ziyu Wang, Yuanyuan Wei, et al.
Process Safety and Environmental Protection (2024) Vol. 191, pp. 2572-2588
Closed Access | Times Cited: 3
Prediction and assessment of the impact of COVID-19 lockdown on air quality over Kolkata: a deep transfer learning approach
Debashree Dutta, Sankar K. Pal
Environmental Monitoring and Assessment (2022) Vol. 195, Iss. 1
Open Access | Times Cited: 13
Machine Learning-Based Wind Speed Estimation for Renewable Energy Optimization in Urban Environments: A Case Study in Kano State, Nigeria
A. M. Ismail, J. M. Umar, J. K. Sagir, et al.
(2024) Vol. 4, Iss. 1, pp. 35-51
Open Access | Times Cited: 2
A Novel Stacking Ensemble Learning Approach for Predicting PM2.5 Levels in Dense Urban Environments Using Meteorological Variables: A Case Study in Macau
Haoting Tian, Hoiio Kong, Chanseng Wong
Applied Sciences (2024) Vol. 14, Iss. 12, pp. 5062-5062
Open Access | Times Cited: 2
A new optimized hybrid approach combining machine learning with WRF-CHIMERE model for PM10 concentration prediction
Youssef Chelhaoui, Khalid El Ass, Mathieu Lachâtre, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 4, pp. 5687-5701
Closed Access | Times Cited: 2
Predicting air quality using random forest: A case study in Amman-Zarqa
Farah Alzu’bi, Abdulla Al-Rawabdeh, Ali Almagbile
The Egyptian Journal of Remote Sensing and Space Science (2024) Vol. 27, Iss. 3, pp. 604-613
Open Access | Times Cited: 2
Evaluation of Machine Learning Models in Air Pollution Prediction for a Case Study of Macau as an Effort to Comply with UN Sustainable Development Goals
Thomas M. T. Lei, Jianxiu Cai, Altaf Hossain Molla, et al.
Sustainability (2024) Vol. 16, Iss. 17, pp. 7477-7477
Open Access | Times Cited: 2
Identification of Factors Influencing Episodes of High PM10 Concentrations in the Air in Krakow (Poland) Using Random Forest Method
Tomasz Gorzelnik, Marek Bogacki, Robert Oleniacz
Sustainability (2024) Vol. 16, Iss. 20, pp. 9015-9015
Open Access | Times Cited: 2
The Relationship between Roadside PM Concentration and Traffic Characterization: A Case Study in Macao
Thomas M. T. Lei, Fred C. Martin
Sustainability (2023) Vol. 15, Iss. 14, pp. 10993-10993
Open Access | Times Cited: 4
Machine Learning Models to Classify Shiitake Mushrooms (Lentinula edodes) According to Their Geographical Origin Labeling
Raquel Rodríguez‐Fernández, Ángela Fernández-Gómez, J. C. Mejuto, et al.
Foods (2024) Vol. 13, Iss. 17, pp. 2656-2656
Open Access | Times Cited: 1
Analyzing meteorological factors for forecasting PM10 and PM2.5 levels: a comparison between MLR and MLP models
Nastaran Talepour, Yaser Tahmasebi Birgani, Frank J. Kelly, et al.
Earth Science Informatics (2024)
Closed Access | Times Cited: 1
Machine learning for air quality index (AQI) forecasting: shallow learning or deep learning?
Elham Kalantari, Hamid Gholami, Hossein Malakooti, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 54, pp. 62962-62982
Closed Access | Times Cited: 1
An Ensemble Model with Adaptive Variational Mode Decomposition and Multivariate Temporal Graph Neural Network for PM2.5 Concentration Forecasting
Yadong Pei, Chiou‐Jye Huang, Yamin Shen, et al.
Sustainability (2022) Vol. 14, Iss. 20, pp. 13191-13191
Open Access | Times Cited: 7
Comparison of Statistical and Deep Learning Methods for Forecasting PM<sub>2.5</sub> Concentration in Northern Thailand
Weerinrada Wongrin, Kuntalee Chaisee, Kamonrat Suphawan
Polish Journal of Environmental Studies (2023) Vol. 32, Iss. 2, pp. 1419-1431
Open Access | Times Cited: 3
Convolutional neural network-based deep learning model for air quality prediction in October city of Egypt
Nehal Elshaboury, Eslam Mohammed Abdelkader, Abobakr Al-Sakkaf
Construction Innovation (2023) Vol. 25, Iss. 2, pp. 620-640
Closed Access | Times Cited: 2
Air Quality Research Based on B-Spline Functional Linear Model: A Case Study of Fujian Province, China
Yihan Xu, Tiange You, Yuanyao Wen, et al.
Applied Sciences (2023) Vol. 13, Iss. 20, pp. 11206-11206
Open Access | Times Cited: 2
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