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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:

Optimization research on air quality numerical model forecasting effects based on deep learning methods
Wei Wang, Xingqin An, Qingyong Li, et al.
Atmospheric Research (2022) Vol. 271, pp. 106082-106082
Closed Access | Times Cited: 23

Showing 23 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: 127
Deep-AIR: A Hybrid CNN-LSTM Framework for Fine-Grained Air Pollution Estimation and Forecast in Metropolitan Cities
Qi Zhang, Yang Han, Victor O. K. Li, et al.
IEEE Access (2022) Vol. 10, pp. 55818-55841
Open Access | Times Cited: 46
Novel hybrid multi-head self-attention and multifractal algorithm for non-stationary time series prediction
Xiang Yu, DONGMEI ZHANG, Tianqing Zhu, et al.
Information Sciences (2022) Vol. 613, pp. 541-555
Closed Access | Times Cited: 34
Using Random Forest to improve EMEP4PL model estimates of daily PM2.5 in Poland
Tetiana Vovk, Maciej Kryza, Małgorzata Werner
Atmospheric Environment (2024) Vol. 332, pp. 120615-120615
Open Access | Times Cited: 4
Air pollutant prediction based on a attention mechanism model of the Yangtze River Delta region in frequent heatwaves
Bingchun Liu, Mingzhao Lai, Peng Zeng, et al.
Atmospheric Research (2024), pp. 107701-107701
Closed Access | Times Cited: 4
State-of-art in modelling particulate matter (PM) concentration: a scoping review of aims and methods
Lorenzo Gianquintieri, Daniele Oxoli, Enrico G. Caiani, et al.
Environment Development and Sustainability (2024)
Open Access | Times Cited: 3
Empowering Energy Access: Exploring Financial Inclusion's Impact on Energy Poverty in the Fragile Five Economies
Xin Xie, Abdülkadir Barut, Kamel Si Mohammed, et al.
Energy (2024), pp. 133184-133184
Closed Access | Times Cited: 3
Computational deep air quality prediction techniques: a systematic review
Manjit Kaur, Dilbag Singh, Mohamed Yaseen Jabarulla, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. S2, pp. 2053-2098
Closed Access | Times Cited: 7
Physical informed neural network improving the WRF-CHEM results of air pollution using satellite-based remote sensing data
Bo Li, Qihou Hu, Meng Gao, et al.
Atmospheric Environment (2023) Vol. 311, pp. 120031-120031
Closed Access | Times Cited: 6
Improving Air Quality Prediction via Self-Supervision Masked Air Modeling
Shuang Chen, He Li, Shinan Shen, et al.
Atmosphere (2024) Vol. 15, Iss. 7, pp. 856-856
Open Access | Times Cited: 1
Vertical distribution and transport characteristics of ozone pollution based on lidar observation network and data assimilation over the Pearl River Delta, China
Ying Pan, Xiang Yan, Chenglei Pei, et al.
Atmospheric Research (2024) Vol. 310, pp. 107643-107643
Closed Access | Times Cited: 1
Predicting plateau atmospheric ozone concentrations by a machine learning approach: A case study of a typical city on the southwestern plateau of China
Qiyao Wang, Huaying Liu, Yingjie Li, et al.
Environmental Pollution (2024) Vol. 363, pp. 125071-125071
Closed Access | Times Cited: 1
CGF: A Category Guidance Based PM$_{2.5}$ Sequence Forecasting Training Framework
Haomin Yu, Jilin Hu, Xinyuan Zhou, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 35, Iss. 10, pp. 10125-10139
Closed Access | Times Cited: 3
Learning Adaptive Probabilistic Models for Uncertainty-Aware Air Pollution Prediction
Zhiyuan Wu, Ning Liu, Guodong Li, et al.
IEEE Access (2023) Vol. 11, pp. 24971-24985
Open Access | Times Cited: 3
Air Quality Prediction using Ensemble Voting based Deep Learning with Mud Ring Algorithm for Intelligent Transportation Systems

Global NEST Journal (2023)
Open Access | Times Cited: 2
A High-Density Digital Environmental Monitoring System for Vehicle Emissions
Vladimir Shepelev, A. I. Vorobyev, Aidar Kurmanov
2022 International Russian Automation Conference (RusAutoCon) (2024), pp. 680-684
Closed Access
An iteratively optimized downscaling method for city-scale air quality forecast emission inventory establishment
Chengwei Lü, Zihang Zhou, Hefan Liu, et al.
The Science of The Total Environment (2024) Vol. 954, pp. 176824-176824
Closed Access
Development of a city-level surface ozone forecasting system using deep learning techniques and air quality model: application in Eastern China
Qianyun Li, Jie Li, Zixi Wang, et al.
Atmospheric Environment (2024) Vol. 339, pp. 120865-120865
Closed Access
DDSNet: A dual-channel dual-mode smoke detection network for lightweight industrial scenarios
Simeng Wang, Chengxu Zhou, Ke Gu, et al.
(2024), pp. 132-137
Closed Access
A Deep Learning-Based Model for Secondary Prediction on Deep-Sea Collector Plumes
Xinyuan Zhou, Yang Yao-min, Ren Yue, et al.
2022 IEEE International Conference on Mechatronics and Automation (ICMA) (2023)
Closed Access | Times Cited: 1
MFF-Net: A multitask feature fusion network in dual-frequency domains for detecting smoke from one single picture
Chengxu Zhou, Ruifang Dong, Mingxing Wang
Displays (2023) Vol. 82, pp. 102576-102576
Closed Access | Times Cited: 1
Modeling the air pollution process using a novel multi-site and multi-scale method with adaptive utilization of spatio-temporal information
Guang Shi, Yee Leung, Jiangshe Zhang, et al.
Chemosphere (2023) Vol. 349, pp. 140799-140799
Closed Access | Times Cited: 1
Optimal Prediction of Air Quality Index in Metropolitan Cities Using Fuzzy Time Series with Deep Learning Approach
Asha Unnikrishnan, S. Rajeswari
Ecological Engineering & Environmental Technology (2023) Vol. 25, Iss. 1, pp. 341-359
Open Access | Times Cited: 1
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