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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 novel hybrid fine particulate matter (PM2.5) forecasting and its further application system: Case studies in China
Pei Du, Jianzhou Wang, Wendong Yang, et al.
Journal of Forecasting (2021) Vol. 41, Iss. 1, pp. 64-85
Closed Access | Times Cited: 22

Showing 22 citing articles:

Artificial Intelligence Technologies for Forecasting Air Pollution and Human Health: A Narrative Review
S. Shankar, Naveenkumar Raju, Abbas Ganesan, et al.
Sustainability (2022) Vol. 14, Iss. 16, pp. 9951-9951
Open Access | Times Cited: 108
Wind power forecasting based on stacking ensemble model, decomposition and intelligent optimization algorithm
Yingchao Dong, Hongli Zhang, Cong Wang, et al.
Neurocomputing (2021) Vol. 462, pp. 169-184
Closed Access | Times Cited: 92
Predicting next hour fine particulate matter (PM2.5) in the Istanbul Metropolitan City using deep learning algorithms with time windowing strategy
Beytullah Eren, İpek Aksangür, Caner Erden
Urban Climate (2023) Vol. 48, pp. 101418-101418
Closed Access | Times Cited: 39
Forecasting hourly PM2.5 concentrations based on decomposition-ensemble-reconstruction framework incorporating deep learning algorithms
Peilei Cai, Chengyuan Zhang, Jian Chai
Data Science and Management (2023) Vol. 6, Iss. 1, pp. 46-54
Open Access | Times Cited: 29
A newly combination model based on data denoising strategy and advanced optimization algorithm for short-term wind speed prediction
Mengzheng Lv, Jianzhou Wang, Xinsong Niu, et al.
Journal of Ambient Intelligence and Humanized Computing (2022) Vol. 14, Iss. 7, pp. 8271-8290
Closed Access | Times Cited: 33
Improving PM2.5 prediction in New Delhi using a hybrid extreme learning machine coupled with snake optimization algorithm
Adil Masood, Mohammed Majeed Hameed, Aman Srivastava, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 20
Wind speed interval prediction model based on variational mode decomposition and multi-objective optimization
Jianzhou Wang, Zishu Cheng
Applied Soft Computing (2021) Vol. 113, pp. 107848-107848
Closed Access | Times Cited: 36
Can place-based policy reduce carbon emissions? Evidence from industrial transformation and upgrading exemplary zone in China
Yuan Feng, Liyuan Wang, Changfei Nie
Humanities and Social Sciences Communications (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 5
A Wavelet PM2.5 Prediction System Using Optimized Kernel Extreme Learning with Boruta-XGBoost Feature Selection
Ali Asghar Heidari, Mehdi Akhoondzadeh, Huiling Chen
Mathematics (2022) Vol. 10, Iss. 19, pp. 3566-3566
Open Access | Times Cited: 22
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
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
Dynamic weighting and genetic algorithm-based hybrid SVR-Ridge model for improving PM 2.5 forecasting in open-pit copper mines
L. T. K. Ngoc, Hoang Nguyen, Xuan-Nam Bui, et al.
International Journal of Mining Reclamation and Environment (2025), pp. 1-31
Closed Access
A deep learning‐based multivariate decomposition and ensemble framework for container throughput forecasting
Anurag Kulshrestha, Abhishek Yadav, Himanshu Sharma, et al.
Journal of Forecasting (2024) Vol. 43, Iss. 7, pp. 2685-2704
Closed Access | Times Cited: 2
PM2.5 prediction and related health effects and economic cost assessments in 2020 and 2021: Case studies in Jing-Jin-Ji, China
Pei Du, Jianzhou Wang, Tong Niu, et al.
Knowledge-Based Systems (2021) Vol. 233, pp. 107487-107487
Closed Access | Times Cited: 15
Volatility index prediction based on a hybrid deep learning system with multi-objective optimization and mode decomposition
Chaonan Tian, Tong Niu, Wei Wei
Expert Systems with Applications (2022) Vol. 213, pp. 119184-119184
Closed Access | Times Cited: 8
The Influence of Data Length on the Performance of Artificial Intelligence Models in Predicting Air Pollution
Mohamed Khalid AlOmar, Faidhalrahman Khaleel, Abdulwahab A. Abdulrahman Al-Saadi, et al.
Advances in Meteorology (2022) Vol. 2022, pp. 1-20
Open Access | Times Cited: 7
Predicting Indoor PM2.5 Concentration using LSTM-BNN in Edge Device
Ida Bagus Krishna Yoga Utama, Duc Hoang Tran, Radityo Fajar Pamungkas, et al.
(2023)
Closed Access | Times Cited: 2
A novel combined multi-variate prediction framework for air pollution based on feature selection and deep learning models
Lu Bai, Pei Du, Shubin Wang, et al.
Process Safety and Environmental Protection (2024)
Closed Access
Time Series Adaptive Mode Decomposition (Tamd): A Method for Improving Time Series Forecasting Accuracy in the Apparel Industry
G. M. Zhou, P. L. Liu, Qing Lin, et al.
(2024)
Closed Access
Multi‐step air quality index forecasting via data preprocessing, sequence reconstruction, and improved multi‐objective optimization algorithm
Ying Wang, Jianzhou Wang, Hongmin Li, et al.
Journal of Forecasting (2022) Vol. 41, Iss. 7, pp. 1483-1511
Closed Access | Times Cited: 2
Efficient Deep Learning-driven Approach for PM2.5 Forecasting at Different Locations in Spain
Abdelkader Dairi, Fouzi Harrou, Ying Sun
(2021), pp. 173-178
Closed Access | Times Cited: 2
Good environmental governance: Predicting PM2.5 by using Spatiotemporal Matrix Factorization generative adversarial network
An Zhang, Sheng Chen, Fen Zhao, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 1
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