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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:

Enhancing PM2.5 Prediction Using NARX-Based Combined CNN and LSTM Hybrid Model
Ahmed Samy AbdElAziz Moursi, Nawal El‐Fishawy, Soufiene Djahel, et al.
Sensors (2022) Vol. 22, Iss. 12, pp. 4418-4418
Open Access | Times Cited: 21

Showing 21 citing articles:

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: 18
Interpreting hourly mass concentrations of PM2.5 chemical components with an optimal deep-learning model
Hongyi Li, Ting Yang, Yiming Du, et al.
Journal of Environmental Sciences (2024) Vol. 151, pp. 125-139
Closed Access | Times Cited: 7
Meteorological Anomalies During Earthquake Preparation: A Case Study for the 1995 Kobe Earthquake (M = 7.3) Based on Statistical and Machine Learning-Based Analyses
Masashi Hayakawa, Shinji Hirooka, Koichiro Michimoto, et al.
Atmosphere (2025) Vol. 16, Iss. 1, pp. 88-88
Open Access
Apply a deep learning hybrid model optimized by an Improved Chimp Optimization Algorithm in PM2.5 prediction
Ming Wei, Xiaopeng Du
Machine Learning with Applications (2025), pp. 100624-100624
Open Access
A hybrid deep learning air pollution prediction approach based on neighborhood selection and spatio-temporal attention
Gang Chen, Chen Shen, Dong Li, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Multi-granularity PM2.5 concentration long sequence prediction model combined with spatial–temporal graph
Bo Zhang, Hong Qin, Yuqi Zhang, et al.
Environmental Modelling & Software (2025), pp. 106400-106400
Closed Access
MSAFormer: A Transformer-Based Model for PM2.5 Prediction Leveraging Sparse Autoencoding of Multi-Site Meteorological Features in Urban Areas
Hongqing Wang, Lifu Zhang, Rong Wu
Atmosphere (2023) Vol. 14, Iss. 8, pp. 1294-1294
Open Access | Times Cited: 7
Prediction of Pollutant Concentration Based on Spatial–Temporal Attention, ResNet and ConvLSTM
Chen Cai, Agen Qiu, Haoyu Chen, et al.
Sensors (2023) Vol. 23, Iss. 21, pp. 8863-8863
Open Access | Times Cited: 7
Prediction of road dust concentration in open-pit coal mines based on multivariate mixed model
Meng Wang, Zongwei Yang, Caiwang Tai, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0284815-e0284815
Open Access | Times Cited: 6
System Identification Methodology of a Gas Turbine Based on Artificial Recurrent Neural Networks
Rubén Aquize, Armando Cajahuaringa, José Antonio Domínguez Machuca, et al.
Sensors (2023) Vol. 23, Iss. 4, pp. 2231-2231
Open Access | Times Cited: 5
HDLP: air quality modeling with hybrid deep learning approaches and particle swam optimization
E. A. Osman, C. Banerjee, Ajeet Singh Poonia
Innovations in Systems and Software Engineering (2024) Vol. 20, Iss. 3, pp. 287-299
Closed Access | Times Cited: 1
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: 1
Forecasting the trend of tuberculosis incidence in Anhui Province based on machine learning optimization algorithm, 2013–2023
Yan Zhang, Huan Ma, Hua Wang, et al.
BMC Pulmonary Medicine (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
An attention-based CNN model integrating observational and simulation data for high-resolution spatial estimation of urban air quality
Shibao Wang, Yanxu Zhang
Atmospheric Environment (2024) Vol. 340, pp. 120921-120921
Closed Access | Times Cited: 1
AI-based prediction of the improvement in air quality induced by emergency measures
Pavithra Pari, Tasneem Abbasi, S. A. Abbasi
Journal of Environmental Management (2023) Vol. 351, pp. 119716-119716
Closed Access | Times Cited: 3
Improvement of LSTM-Based Forecasting with NARX Model through Use of an Evolutionary Algorithm
Cătălina Cocianu, Cristian Răzvan Uscatu, Mihai Avramescu
Electronics (2022) Vol. 11, Iss. 18, pp. 2935-2935
Open Access | Times Cited: 5
Predicting Indoor PM2.5 Concentration using LSTM-BNN in Edge Device
Ida Bagus Krishna Yoga Utama, Duc Hoang Tran, Radityo Fajar Pamungkas, et al.
(2023)
Closed Access | Times Cited: 2
Monitoring and Prediction of Particulate Matter (PM2.5 and PM10) around the Ipbeja Campus
Flávia Matias Oliveira da Silva, Eduardo Carlos Alexandrina, Ana Pardal, et al.
Sustainability (2022) Vol. 14, Iss. 24, pp. 16892-16892
Open Access | Times Cited: 4
Generative Representation Learning in Recurrent Neural Networks for Causal Timeseries Forecasting
Georgios Chatziparaskevas, Ioannis Mademlis, Ioannis Pitas
IEEE Transactions on Artificial Intelligence (2024) Vol. 5, Iss. 12, pp. 6412-6425
Closed Access
Analysis of Spatio-Temporal Characteristics and Trend Forecast of Building Industry VOCs Emissions in China
Hongbin Dai, Guangqiu Huang, Jingjing Wang, et al.
Buildings (2022) Vol. 12, Iss. 10, pp. 1661-1661
Open Access | Times Cited: 2
Deep learning algorithms for air pollution forecasting: an overview of recent developments
Hailong Shu, Zhen Song, Huichuang Guo, et al.
(2023), pp. 19-19
Closed Access
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