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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:

Forecasting hourly PM2.5 based on deep temporal convolutional neural network and decomposition method
Fuxin Jiang, Chengyuan Zhang, Shaolong Sun, et al.
Applied Soft Computing (2021) Vol. 113, pp. 107988-107988
Closed Access | Times Cited: 39

Showing 1-25 of 39 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
Decomposition integration and error correction method for photovoltaic power forecasting
Guohui Li, Xuan Wei, Hong Yang
Measurement (2023) Vol. 208, pp. 112462-112462
Closed Access | Times Cited: 53
Water quality prediction in the Yellow River source area based on the DeepTCN-GRU model
Qingqing Tian, Wei Luo, Lei Guo
Journal of Water Process Engineering (2024) Vol. 59, pp. 105052-105052
Closed Access | Times Cited: 21
Deep-learning architecture for PM2.5 concentration prediction: A review
Shiyun Zhou, Wei Wang, Long Zhu, et al.
Environmental Science and Ecotechnology (2024) Vol. 21, pp. 100400-100400
Open Access | Times Cited: 18
A self-attention-LSTM method for dam deformation prediction based on CEEMDAN optimization
Shuo Cai, Huixin Gao, Jie Zhang, et al.
Applied Soft Computing (2024) Vol. 159, pp. 111615-111615
Closed Access | Times Cited: 16
Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network
Zhenfang He, Qingchun Guo, Zhaosheng Wang, et al.
Atmosphere (2022) Vol. 13, Iss. 8, pp. 1221-1221
Open Access | Times Cited: 55
Machine learning and deep learning modeling and simulation for predicting PM2.5 concentrations
Jian Peng, Haisheng Han, Yong Yi, et al.
Chemosphere (2022) Vol. 308, pp. 136353-136353
Closed Access | Times Cited: 53
Prediction of CO concentration in different conditions based on Gaussian-TCN
Sen Ni, Pengfei Jia, Xu Yang, et al.
Sensors and Actuators B Chemical (2022) Vol. 376, pp. 133010-133010
Closed Access | Times Cited: 48
Combined Ultra-Short-Term Photovoltaic Power Prediction Based on CEEMDAN Decomposition and RIME Optimized AM-TCN-BiLSTM
Daixuan Zhou, Yujin Liu, Xu Wang, et al.
Energy (2025), pp. 134847-134847
Closed Access | Times Cited: 1
A novel decomposition integration model for power coal price forecasting
Siping Wu, Guilin Xia, Lang Liu
Resources Policy (2023) Vol. 80, pp. 103259-103259
Closed Access | Times Cited: 21
Incorporating Temporal Multi-Head Self-Attention Convolutional Networks and LightGBM for Indoor Air Quality Prediction
Yifeng Lu, Jinyong Wang, Dongsheng Wang, et al.
Applied Soft Computing (2024) Vol. 157, pp. 111569-111569
Closed Access | Times Cited: 7
A novel machine learning-based artificial intelligence method for predicting the air pollution index PM2.5
Lingxiao Zhao, Zhiyang Li, Leilei Qu
Journal of Cleaner Production (2024) Vol. 468, pp. 143042-143042
Closed Access | Times Cited: 7
RSMformer: an efficient multiscale transformer-based framework for long sequence time-series forecasting
Guoxiang Tong, Zhaoyuan Ge, Dunlu Peng
Applied Intelligence (2024) Vol. 54, Iss. 2, pp. 1275-1296
Closed Access | Times Cited: 6
Fractional order Lorenz based physics informed SARFIMA-NARX model to monitor and mitigate megacities air pollution
Ayaz Hussain Bukhari, Muhammad Asif Zahoor Raja, Muhammad Shoaib, et al.
Chaos Solitons & Fractals (2022) Vol. 161, pp. 112375-112375
Closed Access | Times Cited: 25
Long-term PM2.5 concentrations forecasting using CEEMDAN and deep Transformer neural network
Qiaolin Zeng, Lihui Wang, Songyan Zhu, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 9, pp. 101839-101839
Closed Access | Times Cited: 14
A novel air pollution forecasting, health effects, and economic cost assessment system for environmental management: From a new perspective of the district-level
Wendong Yang, Jingyi Wang, Kai Zhang, et al.
Journal of Cleaner Production (2023) Vol. 417, pp. 138027-138027
Closed Access | Times Cited: 13
An optimized decomposition integration model for deterministic and probabilistic air pollutant concentration prediction considering influencing factors
Fan Yang, Guangqiu Huang
Atmospheric Pollution Research (2024) Vol. 15, Iss. 7, pp. 102144-102144
Closed Access | Times Cited: 5
A hybrid Harris Hawks Optimization with Support Vector Regression for air quality forecasting
Essam H. Houssein, Mohamed Mroueh, Eman M. G. Younis, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Enhancing multi-step air quality prediction with deep learning using residual neural network and adaptive decomposition-based multi-objective optimization
Kun Hu, Jinxing Che, Wenxin Xia, et al.
Expert Systems with Applications (2025), pp. 126969-126969
Closed Access
PM2.5 concentration simulation by hybrid machine learning based on image features
Minjin Ma, Zhijun Zhao, Yuzhan Ma, et al.
Frontiers in Earth Science (2025) Vol. 13
Open Access
Time-Series Data-Driven PM2.5 Forecasting: From Theoretical Framework to Empirical Analysis
Chengqian Wu, Ruiyang Wang, Siyu Lu, et al.
Atmosphere (2025) Vol. 16, Iss. 3, pp. 292-292
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
Prediction of PM2.5 concentration based on improved secondary decomposition and CSA-KELM
Guohui Li, Ling Chen, Hong Yang
Atmospheric Pollution Research (2022) Vol. 13, Iss. 7, pp. 101455-101455
Closed Access | Times Cited: 15
PM2.5 concentration prediction using weighted CEEMDAN and improved LSTM neural network
Li Zhang, Jinlan Liu, Yuhan Feng, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 30, pp. 75104-75115
Open Access | Times Cited: 7
Synergistic data fusion of satellite observations and in-situ measurements for hourly PM2.5 estimation based on hierarchical geospatial long short-term memory
Xinyu Yu, Man Sing Wong, Chun‐Ho Liu, et al.
Atmospheric Environment (2022) Vol. 286, pp. 119257-119257
Closed Access | Times Cited: 11
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