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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:

Development of a high-performance machine learning model to predict ground ozone pollution in typical cities of China
Yong Cheng, Lingyan He, Xiaofeng Huang
Journal of Environmental Management (2021) Vol. 299, pp. 113670-113670
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Deep learning for air pollutant concentration prediction: A review
Bo Zhang, Yi Rong, Ruihan Yong, et al.
Atmospheric Environment (2022) Vol. 290, pp. 119347-119347
Closed Access | Times Cited: 125
Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign
Bin Guo, Haojie Wu, Lin Pei, et al.
Environment International (2022) Vol. 170, pp. 107606-107606
Open Access | Times Cited: 48
Graph convolutional network – Long short term memory neural network- multi layer perceptron- Gaussian progress regression model: A new deep learning model for predicting ozone concertation
Mohammad Ehteram, Ali Najah Ahmed, Zohreh Sheikh Khozani, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 6, pp. 101766-101766
Open Access | Times Cited: 36
A comparison of machine learning methods for ozone pollution prediction
Qilong Pan, Fouzi Harrou, Ying Sun
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 30
Efficient ozone concentration trend prediction using ANN and K-means clustering
Jun-Bum Park
Earth Science Informatics (2025) Vol. 18, Iss. 1
Closed Access | Times Cited: 1
A comprehensive evaluation of deep learning approaches for ground-level ozone prediction across different regions
Guanjun Lin, Hang Zhao, Yufeng Chi
Ecological Informatics (2025), pp. 103024-103024
Open Access | Times Cited: 1
A deep learning model integrating a wind direction-based dynamic graph network for ozone prediction
Shi‐Yi Wang, Yiming Sun, Gu Hongya, et al.
The Science of The Total Environment (2024) Vol. 946, pp. 174229-174229
Closed Access | Times Cited: 6
Ozone concentration forecasting utilizing leveraging of regression machine learnings: A case study at Klang Valley, Malaysia
Sarmad Dashti Latif, Vivien Lai, Farah Hazwani Hahzaman, et al.
Results in Engineering (2024) Vol. 21, pp. 101872-101872
Open Access | Times Cited: 5
Prediction of respiratory diseases based on random forest model
Xiaotong Yang, Yi Li, Lang Liu, et al.
Frontiers in Public Health (2025) Vol. 13
Open Access
An Efficient Modern Convolution-Based Dynamic Spatiotemporal Deep Learning Architecture for Ozone Prediction
Ao Li, Li Ji, Zhizhang Shen
Environmental Modelling & Software (2025), pp. 106424-106424
Closed Access
Enhancing Time Resolution of Ambient VOC Measurement Data by Machine Learning: From One‐Hour to Five Minutes
Yong Cheng, Xiaofeng Huang, Peng Yan, et al.
Journal of Geophysical Research Atmospheres (2025) Vol. 130, Iss. 5
Closed Access
Long time series ozone prediction in China: A novel dynamic spatiotemporal deep learning approach
Wenjing Mao, Limin Jiao, Weilin Wang
Building and Environment (2022) Vol. 218, pp. 109087-109087
Closed Access | Times Cited: 19
Explainable and spatial dependence deep learning model for satellite-based O3 monitoring in China
Nana Luo, Zhou Zang, Chuan Yin, et al.
Atmospheric Environment (2022) Vol. 290, pp. 119370-119370
Open Access | Times Cited: 19
Predicting the long-term CO2 concentration in classrooms based on the BO–EMD–LSTM model
Guangfei Yang, Erbiao Yuan, Wenjun Wu
Building and Environment (2022) Vol. 224, pp. 109568-109568
Closed Access | Times Cited: 17
A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter
Fang Li, Jianbing Jin, Arjo Segers, et al.
Geoscientific model development (2023) Vol. 16, Iss. 16, pp. 4867-4882
Open Access | Times Cited: 8
A High-Performance Convolutional Neural Network for Ground-Level Ozone Estimation in Eastern China
Sichen Wang, Yanfeng Huo, Xidong Mu, et al.
Remote Sensing (2022) Vol. 14, Iss. 7, pp. 1640-1640
Open Access | Times Cited: 13
The nonlinear relationship between air quality and housing prices by machine learning
Weiwen Zhang, Sheng Pan, Zhiyuan Li, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 53, pp. 114375-114390
Closed Access | Times Cited: 7
A hybrid water quality prediction model based on variational mode decomposition and bidirectional gated recursive unit
Jiange Jiao, Qianqian Ma, Senjun Huang, et al.
Water Science & Technology (2024) Vol. 89, Iss. 9, pp. 2273-2289
Open Access | Times Cited: 2
Clustering-based spatial transfer learning for short-term ozone forecasting
Tuo Deng, Astrid Manders, Jianbing Jin, et al.
Journal of Hazardous Materials Advances (2022) Vol. 8, pp. 100168-100168
Open Access | Times Cited: 12
The spatiotemporal pattern of surface ozone and its impact on agricultural productivity in China
Xiaoguang Chen, Jing Gao, Luoye Chen, et al.
PNAS Nexus (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 6
Performance evaluation of whey flux in dead-end and cross-flow modes via convolutional neural networks
Lukka Thuyavan Yogarathinam, Kirubakaran Velswamy, G. Arthanareeswaran, et al.
Journal of Environmental Management (2021) Vol. 301, pp. 113872-113872
Closed Access | Times Cited: 14
Association analysis between socioeconomic factors and urban ozone pollution in China
Guangfei Yang, Yuhong Liu, Wenli Li, et al.
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 7, pp. 17597-17611
Closed Access | Times Cited: 8
Transformer-based ozone multivariate prediction considering interpretable and priori knowledge: A case study of Beijing, China
Liangliang Mu, Suhuan Bi, Xiangqian Ding, et al.
Journal of Environmental Management (2024) Vol. 366, pp. 121883-121883
Closed Access | Times Cited: 1
Investigation of spatiotemporal distribution and formation mechanisms of ozone pollution in eastern Chinese cities applying convolutional neural network
Qiaoli Wang, Dongping Sheng, Chengzhi Wu, et al.
Journal of Environmental Sciences (2023) Vol. 148, pp. 126-138
Closed Access | Times Cited: 4
Simulation of the Ozone Concentration in Three Regions of Xinjiang, China, Using a Genetic Algorithm-Optimized BP Neural Network Model
Qilong Zhao, Kui Jiang, Dilinuer Talifu, et al.
Atmosphere (2023) Vol. 14, Iss. 1, pp. 160-160
Open Access | Times Cited: 3
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