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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.

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Showing 1-25 of 47 citing articles:

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: 333
Predicting of Daily PM2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China
Qingchun Guo, Zhenfang He, Zhaosheng Wang
Toxics (2023) Vol. 11, Iss. 1, pp. 51-51
Open Access | Times Cited: 55
Hybridization of hybrid structures for time series forecasting: a review
Zahra Hajirahimi, Mehdi Khashei
Artificial Intelligence Review (2022) Vol. 56, Iss. 2, pp. 1201-1261
Closed Access | Times Cited: 66
Influence and prediction of PM2.5 through multiple environmental variables in China
Haoyu Jin, Xiaohong Chen, Ruida Zhong, et al.
The Science of The Total Environment (2022) Vol. 849, pp. 157910-157910
Closed Access | Times Cited: 60
Multi-step forecast of PM2.5 and PM10 concentrations using convolutional neural network integrated with spatial–temporal attention and residual learning
Kefei Zhang, Xiaolin Yang, Hua Cao, et al.
Environment International (2022) Vol. 171, pp. 107691-107691
Open Access | Times Cited: 50
24-Hour prediction of PM2.5 concentrations by combining empirical mode decomposition and bidirectional long short-term memory neural network
Mengfan Teng, Siwei Li, Jia Xing, et al.
The Science of The Total Environment (2022) Vol. 821, pp. 153276-153276
Open Access | Times Cited: 43
A new ensemble spatio-temporal PM2.5 prediction method based on graph attention recursive networks and reinforcement learning
Jing Tan, Hui Liu, Yanfei Li, et al.
Chaos Solitons & Fractals (2022) Vol. 162, pp. 112405-112405
Closed Access | Times Cited: 42
Forecasting air pollutant concentration using a novel spatiotemporal deep learning model based on clustering, feature selection and empirical wavelet transform
Jusong Kim, Xiaoli Wang, Chollyong Kang, et al.
The Science of The Total Environment (2021) Vol. 801, pp. 149654-149654
Closed Access | Times Cited: 44
A hybrid cloud detection and cloud phase classification algorithm using classic threshold-based tests and extra randomized tree model
Huazhe Shang, Husi Letu, Xu Ri, et al.
Remote Sensing of Environment (2023) Vol. 302, pp. 113957-113957
Closed Access | Times Cited: 16
A novel BiGRU multi-step wind power forecasting approach based on multi-label integration random forest feature selection and neural network clustering
Zheyong Jiang, Qingmei Tan, Nan Li, et al.
Energy Conversion and Management (2024) Vol. 319, pp. 118904-118904
Closed Access | Times Cited: 7
The Significant Contribution of Small-Sized and Spherical Aerosol Particles to the Decreasing Trend in Total Aerosol Optical Depth over Land from 2003 to 2018
Ke Gui, Huizheng Che, Lei Li, et al.
Engineering (2021) Vol. 16, pp. 82-92
Open Access | Times Cited: 39
A spatial multi-resolution multi-objective data-driven ensemble model for multi-step air quality index forecasting based on real-time decomposition
Hui Liu, Rui Yang
Computers in Industry (2021) Vol. 125, pp. 103387-103387
Closed Access | Times Cited: 36
A combined forecasting system based on multi-objective optimization and feature extraction strategy for hourly PM2.5 concentration
Jianzhou Wang, Rui Wang, Zhiwu Li
Applied Soft Computing (2021) Vol. 114, pp. 108034-108034
Closed Access | Times Cited: 34
Stage response of vegetation dynamics to urbanization in megacities: A case study of Changsha City, China
Tao Hu, Jianquan Dong, Yi’na Hu, et al.
The Science of The Total Environment (2022) Vol. 858, pp. 159659-159659
Closed Access | Times Cited: 26
Residual neural network with spatiotemporal attention integrated with temporal self-attention based on long short-term memory network for air pollutant concentration prediction
Dong Li, Jian Wang, Dongwei Tian, et al.
Atmospheric Environment (2024) Vol. 329, pp. 120531-120531
Closed Access | Times Cited: 5
A Deep Learning Approach for Air Pollution Classification Using InceptionV3 with Transfer Learning
M. M. Pavikars, R. Jansi
Aerosol Science and Engineering (2025)
Closed Access
Including the feature of appropriate adjacent sites improves the PM2.5 concentration prediction with long short-term memory neural network model
Mengfan Teng, Siwei Li, Ge Song, et al.
Sustainable Cities and Society (2021) Vol. 76, pp. 103427-103427
Open Access | Times Cited: 28
Detection of forest fires and pollutant plume dispersion using IoT air quality sensors
Adisorn Lertsinsrubtavee, Thongchai Kanabkaew, Sunee Raksakietisak
Environmental Pollution (2023) Vol. 338, pp. 122701-122701
Closed Access | Times Cited: 11
Towards cleaner air in Siliguri: A comprehensive study of PM2.5 and PM10 through advance computational forecasting models for effective environmental interventions
Arghadeep Bose, Indrajit Roy Chowdhury
Atmospheric Pollution Research (2023) Vol. 15, Iss. 2, pp. 101976-101976
Closed Access | Times Cited: 9
MGSFformer: A Multi-Granularity Spatiotemporal Fusion Transformer for Air Quality Prediction
Chengqing Yu, Fei Wang, Yilun Wang, et al.
Information Fusion (2024) Vol. 113, pp. 102607-102607
Closed Access | Times Cited: 3
PM2.5 Concentration Forecasting Using Weighted Bi-LSTM and Random Forest Feature Importance-Based Feature Selection
Baekcheon Kim, Eun Kyeong Kim, Seunghwan Jung, et al.
Atmosphere (2023) Vol. 14, Iss. 6, pp. 968-968
Open Access | Times Cited: 8
A combined prediction system for PM2.5 concentration integrating spatio-temporal correlation extracting, multi-objective optimization weighting and non-parametric estimation
Jianzhou Wang, Yuansheng Qian, Yuyang Gao, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 10, pp. 101880-101880
Closed Access | Times Cited: 8
An enhanced hybrid ensemble deep learning approach for forecasting daily PM2.5
Hui Liu, Da-hua Deng
Journal of Central South University (2022) Vol. 29, Iss. 6, pp. 2074-2083
Closed Access | Times Cited: 13
Unveiling air pollution patterns in Yemen: a spatial–temporal functional data analysis
Mohanned Abduljabbar Hael
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 17, pp. 50067-50095
Open Access | Times Cited: 7
Quantifying uncertainty of marine water quality forecasts for environmental management using a dynamic multi-factor analysis and multi-resolution ensemble approach
Rui Yang, Hui Liu, Yanfei Li
Chemosphere (2023) Vol. 331, pp. 138831-138831
Closed Access | Times Cited: 7
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