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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 crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features
Huizi He, Mei Sun, Xiuming Li, et al.
Energy (2021) Vol. 244, pp. 122706-122706
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Predicting the changes in the WTI crude oil price dynamics using machine learning models
Hasraddin Guliyev, Eldayag Mustafayev
Resources Policy (2022) Vol. 77, pp. 102664-102664
Closed Access | Times Cited: 70
An ensemble dynamic self-learning model for multiscale carbon price forecasting
Wen Zhang, Zhibin Wu, Xiao‐Jun Zeng, et al.
Energy (2022) Vol. 263, pp. 125820-125820
Open Access | Times Cited: 40
Green finance and the socio-politico-economic factors’ impact on the future oil prices: Evidence from machine learning
Muhammad Mohsin, Fouad Jamaani
Resources Policy (2023) Vol. 85, pp. 103780-103780
Closed Access | Times Cited: 31
A sentiment-enhanced hybrid model for crude oil price forecasting
Yan Fang, Wenyan Wang, Pengcheng Wu, et al.
Expert Systems with Applications (2022) Vol. 215, pp. 119329-119329
Closed Access | Times Cited: 36
Interval prediction approach to crude oil price based on three-way clustering and decomposition ensemble learning
Bingzhen Sun, Juncheng Bai, Xiaoli Chu, et al.
Applied Soft Computing (2022) Vol. 123, pp. 108933-108933
Closed Access | Times Cited: 32
Analysis of financial pressure impacts on the health care industry with an explainable machine learning method: China versus the USA
Futian Weng, Jianping Zhu, Cai Yang, et al.
Expert Systems with Applications (2022) Vol. 210, pp. 118482-118482
Closed Access | Times Cited: 30
A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models
Jawaria Nasir, Muhammad Aamir, Zahoor Ul Haq, et al.
IEEE Access (2023) Vol. 11, pp. 14322-14339
Open Access | Times Cited: 21
Role of Economic Policy Uncertainty in Energy Commodities Prices Forecasting: Evidence from a Hybrid Deep Learning Approach
Amar Rao, Marco Tedeschi, Kamel Si Mohammed, et al.
Computational Economics (2024) Vol. 64, Iss. 6, pp. 3295-3315
Closed Access | Times Cited: 6
Creating a cutting-edge neurocomputing model with high precision
Mahdi Abed Salman, Samaher Al-Janabi
Discover Artificial Intelligence (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 6
Resilience through mineral resource development, oil, and natural resource efficiency: Strengthening economies
Miaoyin Jia, Lu Gan, Youliang Yan, et al.
Resources Policy (2024) Vol. 91, pp. 104942-104942
Closed Access | Times Cited: 5
Machine learning Brent crude oil price forecasts
Bingzi Jin, Xiaojie Xu
Innovation and Emerging Technologies (2024) Vol. 11
Closed Access | Times Cited: 5
A combined model using secondary decomposition for crude oil futures price and volatility forecasting: Analysis based on comparison and ablation experiments
Hao Gong, H. Y. Xing, Yuanyuan Yu, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124196-124196
Closed Access | Times Cited: 4
Analyzing nonlinear and asymmetric effects of green finance and renewable energy on energy efficiency amidst technological innovation in E7 countries
Mingda Shi, Jing Yu
Heliyon (2024) Vol. 10, Iss. 16, pp. e35895-e35895
Open Access | Times Cited: 4
Development and Evaluation of Predictive Machine Learning Models for Crude Oil Supply Chain Logistics in the USA
Maame Korkor Prah, Amina Yakubu, Lawrence Simon Attah, et al.
Technology and Investment (2025) Vol. 16, Iss. 02, pp. 68-78
Open Access
A study of crude oil futures price volatility based on multi-dimensional data from event-driven and deep learning perspectives
Jun Wang, Wenjin Zhao, Fu-Sheng Tsai, et al.
Applied Soft Computing (2023) Vol. 146, pp. 110548-110548
Closed Access | Times Cited: 8
A Supply Chain-Oriented Model to Predict Crude Oil Import Prices in South Korea Based on the Hybrid Approach
Jisung Jo, Umji Kim, Eon-Kyung Lee, et al.
Sustainability (2023) Vol. 15, Iss. 24, pp. 16725-16725
Open Access | Times Cited: 6
Modeling crude oil volatility using economic sentiment analysis and opinion mining of investors via deep learning and machine learning models
Wei Wu, Meiqi Xu, Ruiqian Su, et al.
Energy (2023) Vol. 289, pp. 130017-130017
Closed Access | Times Cited: 6
Do the US president's tweets better predict oil prices? An empirical examination using long short-term memory networks
Stephanie Beyer Díaz, Kristof Coussement, Arno De Caigny, et al.
International Journal of Production Research (2023) Vol. 62, Iss. 6, pp. 2158-2175
Closed Access | Times Cited: 5
Application of Traditional Machine Learning Models for Quantitative Trading of Bitcoin
Yimeng Wang, Keyue Yan
Artificial Intelligence Evolution (2023), pp. 34-48
Open Access | Times Cited: 4
Topology Approach for Crude Oil Price Forecasting of Particle Swarm Optimization and Long Short-Term Memory
Marina Yusoff, Darul Ehsan, Muhammad Sharif, et al.
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Prediction of Weekly Price Trend of Garlic Based on Classification Algorithm and Combined Features
Feihu Sun, Xianyong Meng, Hongqi Zhang, et al.
Horticulturae (2024) Vol. 10, Iss. 4, pp. 347-347
Open Access | Times Cited: 1
A hybrid model based on iTransformer for risk warning of crude oil price fluctuations
Jinchao Li, Yang Guo
Energy (2024), pp. 134199-134199
Closed Access | Times Cited: 1
Artificial Intelligence Techniques for the Forecasting of Crude Oil Price: A Literature Review
Naji Ahmed Mohamed, Mourad Messaadia
(2023)
Closed Access | Times Cited: 2
Research on ERS point registration of large-size measurement field based on neural network non-uniform temperature field
Lulu Huang, Xiang Huang, Shuanggao Li
Robotic Intelligence and Automation (2023) Vol. 43, Iss. 2, pp. 175-190
Closed Access | Times Cited: 2
Exploring the interplay: Crude oil futures, economic shocks, and China's resources
Xiufeng Wang, Yiyun Jiang, G Mányi
Resources Policy (2024) Vol. 91, pp. 104837-104837
Closed Access
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