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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 prediction model based on decomposition-integration and error correction for COVID-19 daily confirmed and death cases
Hong Yang, Heng Liu, Guohui Li
Computers in Biology and Medicine (2023) Vol. 156, pp. 106674-106674
Open Access | Times Cited: 11

Showing 11 citing articles:

Prediction method of PM2.5 concentration based on decomposition and integration
Hong Yang, Wenqian Wang, Guohui Li
Measurement (2023) Vol. 216, pp. 112954-112954
Closed Access | Times Cited: 28
A parallel differential learning ensemble framework based on enhanced feature extraction and anti-information leakage mechanism for ultra-short-term wind speed forecast
Jujie Wang, Yafen Liu, Yaning Li
Applied Energy (2024) Vol. 361, pp. 122909-122909
Closed Access | Times Cited: 6
Enhanced monthly streamflow prediction using an input–output bi-decomposition data driven model considering meteorological and climate information
Qiucen Guo, Xuehua Zhao, Yuhang Zhao, et al.
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 8, pp. 3059-3077
Closed Access | Times Cited: 5
A dual decomposition integration and error correction model for carbon price prediction
Yanan Li, Xinsheng Zhang, Minghu Wang
Journal of Environmental Management (2025) Vol. 374, pp. 124035-124035
Closed Access
Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolitan cities using deep learning models
Sungwook Jung
Digital Health (2025) Vol. 11
Open Access
A multi-factor forecasting model for carbon emissions based on decomposition and swarm intelligence optimization
Hong Yang, Maozhu Wang, Guohui Li
Measurement (2023) Vol. 222, pp. 113554-113554
Closed Access | Times Cited: 12
Advances in artificial intelligence for accurate and timely diagnosis of COVID-19: A comprehensive review of medical imaging analysis
Youssra El Idrissi El-Bouzaidi, Otman Abdoun
Scientific African (2023) Vol. 22, pp. e01961-e01961
Open Access | Times Cited: 12
Forecasting of Indian tourism industry using modeling approach
Renuka Devi, Alok Agrawal, Joydip Dhar, et al.
MethodsX (2024) Vol. 12, pp. 102723-102723
Open Access | Times Cited: 1
A novel honey badger algorithm with multilayer perceptron for predicting COVID-19 time series data
Sultan Noman Qasem
The Journal of Supercomputing (2023) Vol. 80, Iss. 3, pp. 3943-3969
Closed Access | Times Cited: 4
An attention mechanism based deep nonlinear ensemble paradigm of strengthened feature extraction method for wind power prediction
Jujie Wang, Yafen Liu
Journal of Renewable and Sustainable Energy (2023) Vol. 15, Iss. 6
Closed Access
Multi-step influenza forecasting through singular value decomposition and kernel ridge regression with MARCOS-guided gradient-based optimization
Guo Hong-liang, Zhiyao Zhang, Iman Ahmadianfar, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107888-107888
Closed Access
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