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:
A Complete Air Pollution Monitoring and Prediction Framework
Jovan Kalajdjieski, Kire Trivodaliev, Georgina Mirceva, et al.
IEEE Access (2023) Vol. 11, pp. 88730-88744
Open Access | Times Cited: 7
Jovan Kalajdjieski, Kire Trivodaliev, Georgina Mirceva, et al.
IEEE Access (2023) Vol. 11, pp. 88730-88744
Open Access | Times Cited: 7
Showing 7 citing articles:
Real-time IoT-powered AI system for monitoring and forecasting of air pollution in industrial environment
Montaser N.A. Ramadan, Mohammed A. H. Ali, Shin Yee Khoo, et al.
Ecotoxicology and Environmental Safety (2024) Vol. 283, pp. 116856-116856
Open Access | Times Cited: 19
Montaser N.A. Ramadan, Mohammed A. H. Ali, Shin Yee Khoo, et al.
Ecotoxicology and Environmental Safety (2024) Vol. 283, pp. 116856-116856
Open Access | Times Cited: 19
Methods for Urban Air Pollution Measurement and Forecasting: Challenges, Opportunities, and Solutions
Elena Mitreska Jovanovska, Victoria Batz, Petre Lameski, et al.
Atmosphere (2023) Vol. 14, Iss. 9, pp. 1441-1441
Open Access | Times Cited: 19
Elena Mitreska Jovanovska, Victoria Batz, Petre Lameski, et al.
Atmosphere (2023) Vol. 14, Iss. 9, pp. 1441-1441
Open Access | Times Cited: 19
A Deep Learning Approach for Air Pollution Classification Using InceptionV3 with Transfer Learning
M. M. Pavikars, R. Jansi
Aerosol Science and Engineering (2025)
Closed Access
M. M. Pavikars, R. Jansi
Aerosol Science and Engineering (2025)
Closed Access
Exploiting synthetic data generation to enhance pollution prediction
Juan Morales-García, Emilio Ramos-Sorroche, Sara Balderas-Díaz, et al.
Applied Soft Computing (2025), pp. 113076-113076
Closed Access
Juan Morales-García, Emilio Ramos-Sorroche, Sara Balderas-Díaz, et al.
Applied Soft Computing (2025), pp. 113076-113076
Closed Access
A novel artificial intelligence algorithm for predicting air quality by analysing the pollutant levels in air quality data in tamilnadu
P. Aruna Rani, V. Sampathkumar
e-Prime - Advances in Electrical Engineering Electronics and Energy (2023) Vol. 5, pp. 100234-100234
Open Access | Times Cited: 4
P. Aruna Rani, V. Sampathkumar
e-Prime - Advances in Electrical Engineering Electronics and Energy (2023) Vol. 5, pp. 100234-100234
Open Access | Times Cited: 4
A State Monitoring Algorithm for Data Missing Scenarios via Convolutional Neural Network and Random Forest
Yuntao Xu, Kai Sun, Ying Zhang, et al.
IEEE Access (2024) Vol. 12, pp. 137080-137088
Open Access | Times Cited: 1
Yuntao Xu, Kai Sun, Ying Zhang, et al.
IEEE Access (2024) Vol. 12, pp. 137080-137088
Open Access | Times Cited: 1
Forecasting air pollution with deep learning with a focus on impact of urban traffic on PM10 and noise pollution
Martin Kostadinov, Eftim Zdravevski, Petre Lameski, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0313356-e0313356
Open Access | Times Cited: 1
Martin Kostadinov, Eftim Zdravevski, Petre Lameski, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0313356-e0313356
Open Access | Times Cited: 1
