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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:

Predicting next hour fine particulate matter (PM2.5) in the Istanbul Metropolitan City using deep learning algorithms with time windowing strategy
Beytullah Eren, İpek Aksangür, Caner Erden
Urban Climate (2023) Vol. 48, pp. 101418-101418
Closed Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Exploring the nexus between monetary uncertainty and volatility in global crude oil: A contemporary approach of regime-switching
Mengyan Yu, Muhammad Umair, Yessengali Oskenbayev, et al.
Resources Policy (2023) Vol. 85, pp. 103886-103886
Closed Access | Times Cited: 185
Simulating daily PM2.5 concentrations using wavelet analysis and artificial neural network with remote sensing and surface observation data
Qingchun Guo, Zhenfang He, Zhaosheng Wang
Chemosphere (2023) Vol. 340, pp. 139886-139886
Closed Access | Times Cited: 43
Multi-view Stacked CNN-BiLSTM (MvS CNN-BiLSTM) for urban PM2.5 concentration prediction of India’s polluted cities
Subham Kumar, Vipin Kumar
Journal of Cleaner Production (2024) Vol. 444, pp. 141259-141259
Closed Access | Times Cited: 19
Factors evaluation of PM2.5 diffusion in street canyons in Dalian based on numerical simulation
Xiaocheng Song, Yao Zhang, Guoxin Zhang, et al.
Building Simulation (2025)
Closed Access | Times Cited: 2
Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters
Tao Hai, Ali H. Jawad, A.H. Shather, et al.
Environment International (2023) Vol. 175, pp. 107931-107931
Open Access | Times Cited: 30
Comparative Analysis of Multiple Deep Learning Models for Forecasting Monthly Ambient PM2.5 Concentrations: A Case Study in Dezhou City, China
Zhenfang He, Qingchun Guo
Atmosphere (2024) Vol. 15, Iss. 12, pp. 1432-1432
Open Access | Times Cited: 12
Supervised Machine Learning Approaches for Predicting Key Pollutants and for the Sustainable Enhancement of Urban Air Quality: A Systematic Review
Ismail Essamlali, Hasna Nhaila, Mohamed El Khaïli
Sustainability (2024) Vol. 16, Iss. 3, pp. 976-976
Open Access | Times Cited: 11
Hourly PM2.5 concentration prediction for dry bulk port clusters considering spatiotemporal correlation: A novel deep learning blending ensemble model
Jinxing Shen, Q. Liu, Xuejun Feng
Journal of Environmental Management (2024) Vol. 370, pp. 122703-122703
Closed Access | Times Cited: 9
PM2.5 Concentration Prediction Using CNN‐LSTM Model Based on Multi‐Feature Fusion
Zhiwen Wang, Junjian Huang, Junlin Huang, et al.
Concurrency and Computation Practice and Experience (2025) Vol. 37, Iss. 4-5
Closed Access | Times Cited: 1
The application of strategy based on LSTM for the short-term prediction of PM2.5 in city
Min‐Der Lin, Ping‐Yu Liu, Chi‐Wei Huang, et al.
The Science of The Total Environment (2023) Vol. 906, pp. 167892-167892
Closed Access | Times Cited: 18
Air pollution concentration fuzzy evaluation based on evidence theory and the K-nearest neighbor algorithm
Bian Chao, Huang Guang Qiu
Frontiers in Environmental Science (2024) Vol. 12
Open Access | Times Cited: 5
A long-term prediction method for PM2.5 concentration based on spatiotemporal graph attention recurrent neural network and grey wolf optimization algorithm
Chen Zhang, Shengzhao Wang, Yue Wu, et al.
Journal of environmental chemical engineering (2023) Vol. 12, Iss. 1, pp. 111716-111716
Closed Access | Times Cited: 11
Forecasting daily PM2.5 concentrations in Wuhan with a spatial-autocorrelation-based long short-term memory model
Zhifei Liu, C. Ge, Kang Zheng, et al.
Atmospheric Environment (2024) Vol. 331, pp. 120605-120605
Closed Access | Times Cited: 4
Enhancing air pollution prediction: A neural transfer learning approach across different air pollutants
Idriss Jairi, Sarah Ben Othman, Ludivine Canivet, et al.
Environmental Technology & Innovation (2024) Vol. 36, pp. 103793-103793
Open Access | Times Cited: 4
Using the TSA-LSTM two-stage model to predict cancer incidence and mortality
Rabnawaz Khan, Jie Wang
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0317148-e0317148
Open Access
Hybrid Machine Learning to Enhance PM2.5 Forecasting Performance by the WRF-Chem Model
Laddawan Noynoo, Perapong Tekasakul, Thanathip Limna, et al.
Atmospheric Pollution Research (2025), pp. 102558-102558
Closed Access
Variability of the Ground Concentration of Particulate Matter PM1–PM10 in the Air Basin of the Southern Baikal Region
Maxim Y. Shikhovtsev, В. А. Оболкин, Т. В. Ходжер, et al.
Atmospheric and Oceanic Optics (2023) Vol. 36, Iss. 6, pp. 655-662
Closed Access | Times Cited: 10
Modeling PM2.5 urbane pollution using hybrid models incorporating decomposition and multiple factors
Somayeh Mirzaei, Ting Liao, Chin-Yu Hsu
Urban Climate (2025) Vol. 60, pp. 102338-102338
Closed Access
Strategies for sustainable road transport: Technological innovation and organizational management through AI
Yang Liu, Dequn Zhou, Cheng Wu
Transportation Research Part D Transport and Environment (2025) Vol. 141, pp. 104651-104651
Closed Access
PM2.5 probabilistic forecasting system based on graph generative network with graph U-nets architecture
Yanfei Li, Rui Yang, Zhu Duan, et al.
Journal of Central South University (2025) Vol. 32, Iss. 1, pp. 304-318
Closed Access
Elevating Hourly PM2.5 Forecasting in Istanbul, Türkiye: Leveraging ERA5 Reanalysis and Genetic Algorithms in a Comparative Machine Learning Model Analysis
Serdar Gündoğdu, Tolga Elbir
Chemosphere (2024) Vol. 364, pp. 143096-143096
Closed Access | Times Cited: 3
Improving PM10 and PM2.5 concentration prediction using the Brazilian Regional Atmospheric Modeling 5.2 System in Lima, Peru
Odón R. Sánchez-Ccoyllo, Marcelo Félix Alonso
Urban Climate (2024) Vol. 55, pp. 101985-101985
Closed Access | Times Cited: 2
Design and Enhancement of a Fog-Enabled Air Quality Monitoring and Prediction System: An Optimized Lightweight Deep Learning Model for a Smart Fog Environmental Gateway
P. Divya Bharathi, V. Anantha Narayanan, P. Bagavathi Sivakumar
Sensors (2024) Vol. 24, Iss. 15, pp. 5069-5069
Open Access | Times Cited: 2
Prediction of PM2.5 concentration based on a CNN-LSTM neural network algorithm
Xuesong Bai, Na Zhang, Xiaoyi Cao, et al.
PeerJ (2024) Vol. 12, pp. e17811-e17811
Open Access | Times Cited: 2
Uncertainty graph convolution recurrent neural network for air quality forecasting
Dong Mei, Yue Sun, Yutao Jin, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102651-102651
Closed Access | Times Cited: 1
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