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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:

Air quality prediction at new stations using spatially transferred bi-directional long short-term memory network
Jun Ma, Zheng Li, Jack C.P. Cheng, et al.
The Science of The Total Environment (2019) Vol. 705, pp. 135771-135771
Closed Access | Times Cited: 152

Showing 1-25 of 152 citing articles:

A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance
Adil Masood, Kafeel Ahmad
Journal of Cleaner Production (2021) Vol. 322, pp. 129072-129072
Closed Access | Times Cited: 155
Machine learning algorithms to forecast air quality: a survey
Manuel Méndez, Mercedes G. Merayo, Manuel Núñez
Artificial Intelligence Review (2023) Vol. 56, Iss. 9, pp. 10031-10066
Open Access | Times Cited: 135
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
A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network
Cui-Lin Wu, Hong-di He, Rui-feng Song, et al.
Environmental Pollution (2023) Vol. 320, pp. 121075-121075
Closed Access | Times Cited: 46
A multi-source transfer learning model based on LSTM and domain adaptation for building energy prediction
Huiming Lu, Jiazheng Wu, Yingjun Ruan, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 149, pp. 109024-109024
Closed Access | Times Cited: 45
A systematic survey of air quality prediction based on deep learning
Zhen Zhang, Shiqing Zhang, Caimei Chen, et al.
Alexandria Engineering Journal (2024) Vol. 93, pp. 128-141
Open Access | Times Cited: 15
A bi-directional missing data imputation scheme based on LSTM and transfer learning for building energy data
Jun Ma, Jack C.P. Cheng, Feifeng Jiang, et al.
Energy and Buildings (2020) Vol. 216, pp. 109941-109941
Closed Access | Times Cited: 132
A hybrid deep transfer learning strategy for short term cross-building energy prediction
Xi Fang, Guangcai Gong, Guannan Li, et al.
Energy (2020) Vol. 215, pp. 119208-119208
Closed Access | Times Cited: 128
Analyzing driving factors of land values in urban scale based on big data and non-linear machine learning techniques
Jun Ma, Jack C.P. Cheng, Feifeng Jiang, et al.
Land Use Policy (2020) Vol. 94, pp. 104537-104537
Closed Access | Times Cited: 99
RETRACTED ARTICLE: Development of air quality monitoring (AQM) models using different machine learning approaches
C. Amuthadevi, D. S. Vijayan, V. Ramachandran
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 13, Iss. S1, pp. 33-33
Closed Access | Times Cited: 83
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: 79
Prediction of harmful algal blooms in large water bodies using the combined EFDC and LSTM models
Lei Zheng, Huipeng Wang, Liu Cao, et al.
Journal of Environmental Management (2021) Vol. 295, pp. 113060-113060
Closed Access | Times Cited: 78
Identification of the most influential areas for air pollution control using XGBoost and Grid Importance Rank
Jun Ma, Jack C.P. Cheng, Zherui Xu, et al.
Journal of Cleaner Production (2020) Vol. 274, pp. 122835-122835
Closed Access | Times Cited: 72
Investigating photovoltaic solar power output forecasting using machine learning algorithms
Yusuf Essam, Ali Najah Ahmed, Rohaini Ramli, et al.
Engineering Applications of Computational Fluid Mechanics (2022) Vol. 16, Iss. 1, pp. 2002-2034
Open Access | Times Cited: 61
Spatio-attention embedded recurrent neural network for air quality prediction
Yu Huang, Josh Jia-Ching Ying, Vincent S. Tseng
Knowledge-Based Systems (2021) Vol. 233, pp. 107416-107416
Closed Access | Times Cited: 60
Prediction of individual thermal comfort based on ensemble transfer learning method using wearable and environmental sensors
Han-Saem Park, Dong Yoon Park
Building and Environment (2021) Vol. 207, pp. 108492-108492
Closed Access | Times Cited: 55
TLT: Recurrent fine-tuning transfer learning for water quality long-term prediction
Peng Lin, Huan Wu, Min Gao, et al.
Water Research (2022) Vol. 225, pp. 119171-119171
Closed Access | Times Cited: 48
Short-Term Prediction of PM2.5 Using LSTM Deep Learning Methods
Endah Kristiani, Hao Lin, Jwu‐Rong Lin, et al.
Sustainability (2022) Vol. 14, Iss. 4, pp. 2068-2068
Open Access | Times Cited: 46
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: 45
A hybrid deep learning framework for air quality prediction with spatial autocorrelation during the COVID-19 pandemic
Zixi Zhao, Jinran Wu, Fengjing Cai, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 37
Deep learning methods for atmospheric PM2.5 prediction: A comparative study of transformer and CNN-LSTM-attention
Bowen Cui, Minyi Liu, Shanqiang Li, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 9, pp. 101833-101833
Closed Access | Times Cited: 35
Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
Sasikumar Gurumoorthy, Aruna Kumari Kokku, Przemysław Falkowski‐Gilski, et al.
Sustainability (2023) Vol. 15, Iss. 14, pp. 11454-11454
Open Access | Times Cited: 34
Application of robust deep learning models to predict mine water inflow: Implication for groundwater environment management
Songlin Yang, Huiqing Lian, Bin Xu, et al.
The Science of The Total Environment (2023) Vol. 871, pp. 162056-162056
Closed Access | Times Cited: 25
Water quality prediction based on sparse dataset using enhanced machine learning
Huang Sheng, Jun Xia, Yueling Wang, et al.
Environmental Science and Ecotechnology (2024) Vol. 20, pp. 100402-100402
Open Access | Times Cited: 8
Enhancing air pollution mapping with autonomous UAV networks for extended coverage and consistency
Murat Bakırcı
Atmospheric Research (2024) Vol. 306, pp. 107480-107480
Closed Access | Times Cited: 8
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