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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:

A hybrid deep learning technology for PM2.5 air quality forecasting
Zhendong Zhang, Yongkang Zeng, Ke Yan
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 29, pp. 39409-39422
Closed Access | Times Cited: 110

Showing 26-50 of 110 citing articles:

Air quality forecasting using a spatiotemporal hybrid deep learning model based on VMD–GAT–BiLSTM
Xiaohu Wang, Suo Zhang, Yi‐Ping Phoebe Chen, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models
Abbas Pak, Abdullah Kaviani Rad, Mohammad Javad Nematollahi, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Help me summarize a book: user continues to use intentions in AI reading assistants from a generative AI quality viewpoint
Tsung‐Sheng Chang, Dong-Yih Bau
Library Hi Tech (2025)
Closed 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 novel hybrid model based on dual-layer decomposition and kernel density estimation for VOCs concentration forecasting considering influencing factors
Fan Yang, Guangqiu Huang, X. Jiao
Atmospheric Pollution Research (2025), pp. 102439-102439
Closed Access
Air Quality Forecasting in Presence of Missing Data
Zeynep İdil Erzurum Çiçek, Zeliha Ergül Aydın
Communications in computer and information science (2025), pp. 250-261
Closed Access
AI-driven approaches for air pollution modeling: A comprehensive systematic review
Lorenzo Garbagna, Lakshmi Babu Saheer, Mahdi Maktabdar Oghaz
Environmental Pollution (2025), pp. 125937-125937
Closed Access
Air Pollutant Prediction Using Shallow Architecture Machine Learning Algorithms
Moses Olaifa, Vusumuzi Malele
Lecture notes in networks and systems (2025), pp. 461-471
Closed Access
Improving the Spatiotemporal Forecasting of PM2.5 by Coupling a Deep Learning Method with a Chemical Transport Model: A Severe Haze Case in China
Zheng Zhao, Huangjian Wu, Keyi Chen, et al.
Aerosol Science and Engineering (2025)
Closed Access
Deep Learning Neural Network Model for Tunnel Ground Surface Settlement Prediction Based on Sensor Data
Yang Cao, Xiaokang Zhou, Ke Yan
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-14
Open Access | Times Cited: 31
Hourly PM2.5 concentration multi-step forecasting method based on extreme learning machine, boosting algorithm and error correction model
Shi Yin, Hui Liu, Zhu Duan
Digital Signal Processing (2021) Vol. 118, pp. 103221-103221
Closed Access | Times Cited: 29
AQI time series prediction based on a hybrid data decomposition and echo state networks
Hui Liu, Xinyu Zhang
Environmental Science and Pollution Research (2021) Vol. 28, Iss. 37, pp. 51160-51182
Closed Access | Times Cited: 28
An effective integrated genetic programming and neural network model for electronic nose calibration of air pollution monitoring application
Davut Ari, Barış Baykant Alagöz
Neural Computing and Applications (2022) Vol. 34, Iss. 15, pp. 12633-12652
Closed Access | Times Cited: 21
Deep Learning Framework-Based Chaotic Hunger Games Search Optimization Algorithm for Prediction of Air Quality Index
Harshini Macherla, Ghamya Kotapati, Manepalli Tulas Sunitha, et al.
Ingénierie des systèmes d information (2023) Vol. 28, Iss. 2, pp. 433-441
Open Access | Times Cited: 9
A long short-term memory-based hybrid model optimized using a genetic algorithm for particulate matter 2.5 prediction
Anıl Utku, Ümit Can, Mustafa Kamal, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 8, pp. 101836-101836
Closed Access | Times Cited: 9
Multi-source variational mode transfer learning for enhanced PM2.5 concentration forecasting at data-limited monitoring stations
Bozhi Yao, Guang Ling, Feng Liu, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121714-121714
Closed Access | Times Cited: 9
Hazard Susceptibility Mapping with Machine and Deep Learning: A Literature Review
Angelly de Jesus Pugliese Viloria, A. Folini, Daniela Carrión, et al.
Remote Sensing (2024) Vol. 16, Iss. 18, pp. 3374-3374
Open Access | Times Cited: 3
Short-Term Photovoltaic Power Forecasting Based on Historical Information and Deep Learning Methods
Xianchao Guo, Yuchang Mo, Ke Yan
Sensors (2022) Vol. 22, Iss. 24, pp. 9630-9630
Open Access | Times Cited: 14
Temporal Difference-Based Graph Transformer Networks For Air Quality PM2.5 Prediction: A Case Study in China
Zhen Zhang, Shiqing Zhang, Xiaoming Zhao, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 13
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
Air quality prediction using a novel three-stage model based on time series decomposition
Mingyue Sun, Congjun Rao, Zhuo Hu
Environment Development and Sustainability (2024)
Closed Access | Times Cited: 2
An ensemble deep learning approach to spatiotemporal tropospheric ozone forecasting: A case study of Tehran, Iran
Mostafa Rezaali, Mohammad Sina Jahangir, Reza Fouladi Fard, et al.
Urban Climate (2024) Vol. 55, pp. 101950-101950
Closed Access | Times Cited: 2
A novel coupled rainfall prediction model based on stepwise decomposition technique
Xueran Jiao, Zongheng He
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
FMM-VMD-Transformer: A hybrid deep learning model for predicting natural gas consumption
Xinlei Li, Xiaofu Zou, Jiangfeng Cheng, et al.
Digital engineering. (2024) Vol. 2, pp. 100005-100005
Open Access | Times Cited: 2
Time Series Dataset Survey for Forecasting with Deep Learning
Yannik Hahn, Tristan Langer, Richard Meyes, et al.
Forecasting (2023) Vol. 5, Iss. 1, pp. 315-335
Open Access | Times Cited: 6

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