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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 model based on convolutional neural networks and long short-term memory for ozone concentration prediction
Unjin Pak, Chungsong Kim, Unsok Ryu, et al.
Air Quality Atmosphere & Health (2018) Vol. 11, Iss. 8, pp. 883-895
Closed Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

A review of artificial neural network models for ambient air pollution prediction
Sheen Mclean Cabaneros, John Kaiser Calautit, Ben Richard Hughes
Environmental Modelling & Software (2019) Vol. 119, pp. 285-304
Open Access | Times Cited: 386
Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering
Rui Yan, Jiaqiang Liao, Jie Yang, et al.
Expert Systems with Applications (2020) Vol. 169, pp. 114513-114513
Closed Access | Times Cited: 322
A Hybrid CNN-LSTM Model for Forecasting Particulate Matter (PM2.5)
Taoying Li, Miao Hua, Xu Wu
IEEE Access (2020) Vol. 8, pp. 26933-26940
Open Access | Times Cited: 290
Deep learning-based PM2.5 prediction considering the spatiotemporal correlations: A case study of Beijing, China
Unjin Pak, Jun Ma, Unsok Ryu, et al.
The Science of The Total Environment (2019) Vol. 699, pp. 133561-133561
Closed Access | Times Cited: 274
A Short-Term Traffic Flow Prediction Model Based on an Improved Gate Recurrent Unit Neural Network
Wanneng Shu, Ken Cai, Naixue Xiong
IEEE Transactions on Intelligent Transportation Systems (2021) Vol. 23, Iss. 9, pp. 16654-16665
Closed Access | Times Cited: 137
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
Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction
Ellysia Jumin, Nur’atiah Zaini, Ali Najah Ahmed, et al.
Engineering Applications of Computational Fluid Mechanics (2020) Vol. 14, Iss. 1, pp. 713-725
Open Access | Times Cited: 93
A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem
Ali Najah Ahmed, To Van Lam, Nguyễn Duy Hùng, et al.
Applied Soft Computing (2021) Vol. 105, pp. 107282-107282
Closed Access | Times Cited: 82
An Ensemble Model Based on Adaptive Noise Reducer and Over-Fitting Prevention LSTM for Multivariate Time Series Forecasting
Fagui Liu, Muqing Cai, Liangming Wang, et al.
IEEE Access (2019) Vol. 7, pp. 26102-26115
Open Access | Times Cited: 77
A systematic literature review of deep learning neural network for time series air quality forecasting
Nur’atiah Zaini, Lee Woen Ean, Ali Najah Ahmed, et al.
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 4, pp. 4958-4990
Closed Access | Times Cited: 77
A water quality prediction method based on the multi-time scale bidirectional long short-term memory network
Qinghong Zou, Qingyu Xiong, Qiude Li, et al.
Environmental Science and Pollution Research (2020) Vol. 27, Iss. 14, pp. 16853-16864
Closed Access | Times Cited: 74
Regional air quality forecasting using spatiotemporal deep learning
S. Abirami, P. Chitra
Journal of Cleaner Production (2020) Vol. 283, pp. 125341-125341
Closed Access | Times Cited: 73
PM2.5 concentrations forecasting in Beijing through deep learning with different inputs, model structures and forecast time
Jie Yang, Rui Yan, Mingyue Nong, et al.
Atmospheric Pollution Research (2021) Vol. 12, Iss. 9, pp. 101168-101168
Closed Access | Times Cited: 61
Spatiotemporal causal convolutional network for forecasting hourly PM2.5 concentrations in Beijing, China
Lei Zhang, Jiaming Na, Jie Zhu, et al.
Computers & Geosciences (2021) Vol. 155, pp. 104869-104869
Closed Access | Times Cited: 55
New double decomposition deep learning methods for river water level forecasting
A. A. Masrur Ahmed, Ravinesh C. Deo, Afshin Ghahramani, et al.
The Science of The Total Environment (2022) Vol. 831, pp. 154722-154722
Closed Access | Times Cited: 48
A Hybrid Spatiotemporal Deep Model Based on CNN and LSTM for Air Pollution Prediction
Stefan Tsokov, Milena Lazarova, Adelina Aleksieva-Petrova
Sustainability (2022) Vol. 14, Iss. 9, pp. 5104-5104
Open Access | Times Cited: 42
Monitoring and modelling of PM2.5 concentration at subway station construction based on IoT and LSTM algorithm optimization
Xiaohui Guo, Yuanfeng Wang, Shengqi Mei, et al.
Journal of Cleaner Production (2022) Vol. 360, pp. 132179-132179
Closed Access | Times Cited: 38
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
Deep learning coupled model based on TCN-LSTM for particulate matter concentration prediction
Ying Ren, Siyuan Wang, Bisheng Xia
Atmospheric Pollution Research (2023) Vol. 14, Iss. 4, pp. 101703-101703
Closed Access | Times Cited: 24
Integrated thermal error modeling and compensation of machine tool feed system using subtraction-average-based optimizer-based CNN-GRU neural network
Tongtong Yang, Xingwei Sun, Heran Yang, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 131, Iss. 12, pp. 6075-6089
Closed Access | Times Cited: 12
Prediction of air quality in Tehran by developing the nonlinear ensemble model
Aydin Shishegaran, Mohsen Saeedi, Anikender Kumar, et al.
Journal of Cleaner Production (2020) Vol. 259, pp. 120825-120825
Closed Access | Times Cited: 67
A Long Short-Term Memory (LSTM) Network for Hourly Estimation of PM2.5 Concentration in Two Cities of South Korea
Khaula Qadeer, Wajih Ur Rehman, Ahmad Muqeem Sheri, et al.
Applied Sciences (2020) Vol. 10, Iss. 11, pp. 3984-3984
Open Access | Times Cited: 58
Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms
Ayman Yafouz, Ali Najah Ahmed, Nur’atiah Zaini, et al.
Engineering Applications of Computational Fluid Mechanics (2021) Vol. 15, Iss. 1, pp. 902-933
Open Access | Times Cited: 53
A PM2.5 concentration prediction model based on multi-task deep learning for intensive air quality monitoring stations
Qiang Zhang, Shun Wu, Xiangwen Wang, et al.
Journal of Cleaner Production (2020) Vol. 275, pp. 122722-122722
Closed Access | Times Cited: 50
The performance of classification and forecasting Dong Nai River water quality for sustainable water resources management using neural network techniques
Thanh N. Nguyen, Chế Đình Lý, Phạm Văn Tất
Journal of Hydrology (2021) Vol. 596, pp. 126099-126099
Closed Access | Times Cited: 47
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