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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:

Deep-learning architecture for PM2.5 concentration prediction: A review
Shiyun Zhou, Wei Wang, Long Zhu, et al.
Environmental Science and Ecotechnology (2024) Vol. 21, pp. 100400-100400
Open Access | Times Cited: 14

Showing 14 citing articles:

Artificial neural network an innovative approach in air pollutant prediction for environmental applications: A review
Vibha Yadav, Amit Kumar Yadav, Vedant Singh, et al.
Results in Engineering (2024) Vol. 22, pp. 102305-102305
Open Access | Times Cited: 17
Response of Microbial Communities to Antiviral Drug Stress in Surface Water in Beijing
Xin Yuan, Shanwei Sun, Rongshan Wu, et al.
Water (2025) Vol. 17, Iss. 1, pp. 118-118
Open Access | Times Cited: 1
High-Resolution Estimation of Daily PM2.5 Levels in the Contiguous US Using Bi-LSTM with Attention
Zhongying Wang, James Crooks, Elizabeth A. Regan, et al.
Remote Sensing (2025) Vol. 17, Iss. 1, pp. 126-126
Open Access
Short-Sequence Machine Learning Framework for Predicting Constitutive Relationships of Sand
Xiangchen Yao, Shuqi Ma, Bo Li, et al.
Geotechnical and Geological Engineering (2025) Vol. 43, Iss. 2
Closed Access
Synergistic reduction of air pollutants and carbon emissions in Chengdu-Chongqing urban agglomeration, China: Spatial-temporal characteristics, regional differences, and dynamic evolution
Shujiang Xiang, Xianjin Huang, Nana Lin, et al.
Journal of Cleaner Production (2025), pp. 144929-144929
Closed Access
Time-Series Data-Driven PM2.5 Forecasting: From Theoretical Framework to Empirical Analysis
Chengqian Wu, Ruiyang Wang, Siyu Lu, et al.
Atmosphere (2025) Vol. 16, Iss. 3, pp. 292-292
Open Access
Decoding PM2.5 Prediction in Nanning Urban Area, China: Unraveling Model Superiorities and Drawbacks Through SARIMA, Prophet, and LightGBM
Minru Chen, Binglin Liu, Mei Liang, et al.
Algorithms (2025) Vol. 18, Iss. 3, pp. 167-167
Open Access
Dynamic prediction of PM2.5 concertation in China using experience replay with multi-period memory buffers
Haoze Shi, Xin Yang, Hong Tang, et al.
Atmospheric Research (2025), pp. 108063-108063
Closed Access
Toward causal artificial intelligence approach for PM2.5 interpretation: A discovery of structural causal models
Mallika Kliangkhlao, Apaporn Tipsavak, Thanathip Limna, et al.
Ecological Informatics (2025), pp. 103115-103115
Open Access
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: 3
An exploration of urban air health navigation system based on dynamic exposure risk forecast of ambient PM2.5
Pei Jiang, C. Y. Gao, Junrui Zhao, et al.
Environment International (2024) Vol. 190, pp. 108793-108793
Open Access | Times Cited: 1
Probing the capacity of a spatiotemporal deep learning model for short-term PM2.5 forecasts in a coastal urban area
Qi Liao, Mingming Zhu, Lin Wu, et al.
The Science of The Total Environment (2024) Vol. 950, pp. 175233-175233
Closed Access | Times Cited: 1
Performance evaluation of multivariate deep-time convolution neural architectures for short-term electricity forecasting: Findings and failures
Flavian Emmanuel Sapnken, Ali Khalili Tazehkandgheshlagh, Mohammed Hamaidi, et al.
Energy 360. (2024) Vol. 1, pp. 100005-100005
Closed Access | Times Cited: 1
Development of PM2.5 Forecast Model Combining ConvLSTM and DNN in Seoul
Ji-Seok Koo, Kyung-Hui Wang, Hui-Young Yun, et al.
Atmosphere (2024) Vol. 15, Iss. 11, pp. 1276-1276
Open Access | Times Cited: 1
A new attention-based CNN_GRU model for spatial–temporal PM2.5 prediction
Sara Haghbayan, Mehdi Momeni, Behnam Tashayo
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 40, pp. 53140-53155
Closed Access
PR-FCNN: a data-driven hybrid approach for predicting PM2.5 concentration
Syed Azeem Inam, Abdullah Ayub Khan, Tehseen Mazhar, et al.
Discover Artificial Intelligence (2024) Vol. 4, Iss. 1
Open Access
Enhanced PM2.5 Prediction with A Dynamic Wind-Driven Graph Fusion Model Incorporating Inter-Station Pollutant Transport
Haonan Gu, Yinqiao Zhang, Xiaoming Shi, et al.
Atmospheric Environment (2024), pp. 121012-121012
Closed Access
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