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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 method of forecasting crude oil prices using complex network science and artificial intelligence algorithms
Minggang Wang, Longfeng Zhao, Ruijin Du, et al.
Applied Energy (2018) Vol. 220, pp. 480-495
Open Access | Times Cited: 133

Showing 26-50 of 133 citing articles:

Forecasting of Cryptocurrency Prices Using Machine Learning
Vasily Derbentsev, Andriy Matviychuk, Vladimir Soloviev
Springer eBooks (2020), pp. 211-231
Closed Access | Times Cited: 50
A novel method for online real-time forecasting of crude oil price
Yuan Zhao, Weiguo Zhang, Xue Gong, et al.
Applied Energy (2021) Vol. 303, pp. 117588-117588
Closed Access | Times Cited: 47
A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities
Krzysztof Drachal, Michal E. Pawlowski
Economies (2021) Vol. 9, Iss. 1, pp. 6-6
Open Access | Times Cited: 44
Multi-perspective crude oil price forecasting with a new decomposition-ensemble framework
Jingjun Guo, Zhengling Zhao, Jingyun Sun, et al.
Resources Policy (2022) Vol. 77, pp. 102737-102737
Closed Access | Times Cited: 32
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
Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting
Aviral Kumar Tiwari, Gagan Deep Sharma, Amar Rao, et al.
Energy Economics (2024) Vol. 134, pp. 107608-107608
Closed Access | Times Cited: 7
A novel density peaks clustering algorithm based on k nearest neighbors for improving assignment process
Jianhua Jiang, Yujun Chen, Xianqiu Meng, et al.
Physica A Statistical Mechanics and its Applications (2019) Vol. 523, pp. 702-713
Closed Access | Times Cited: 53
Complex Systems Theory and Crashes of Cryptocurrency Market
Vladimir Soloviev, Andriy Belinskiy
Communications in computer and information science (2019), pp. 276-297
Closed Access | Times Cited: 51
Daily natural gas price forecasting by a weighted hybrid data-driven model
Jianliang Wang, Changran Lei, Meiyu Guo
Journal of Petroleum Science and Engineering (2020) Vol. 192, pp. 107240-107240
Closed Access | Times Cited: 40
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
Point and interval forecasting system for crude oil price based on complete ensemble extreme-point symmetric mode decomposition with adaptive noise and intelligent optimization algorithm
Xuerui Wang, Xiangyu Li, Shaoting Li
Applied Energy (2022) Vol. 328, pp. 120194-120194
Closed Access | Times Cited: 24
Seasonal learning based ARIMA algorithm for prediction of Brent oil Price trends
Prasannavenkatesan Theerthagiri, A. Usha Ruby
Multimedia Tools and Applications (2023) Vol. 82, Iss. 16, pp. 24485-24504
Closed Access | Times Cited: 16
Multivariate analysis and forecasting of the crude oil prices: Part I – Classical machine learning approaches
Nishant Nisan Jha, Hemanth Kumar Tanneru, Sridhar Palla, et al.
Energy (2024) Vol. 296, pp. 131185-131185
Closed Access | Times Cited: 5
Mixed-frequency data Sampling Grey system Model: Forecasting annual CO2 emissions in China with quarterly and monthly economic-energy indicators
Yimeng An, Yaoguo Dang, Junjie Wang, et al.
Applied Energy (2024) Vol. 370, pp. 123531-123531
Closed Access | Times Cited: 5
Deep neural networks in chemical engineering classrooms to accurately model adsorption equilibrium data
Shubhangi Kakkar, Witold Kwapiński, Christopher A. Howard, et al.
Education for Chemical Engineers (2021) Vol. 36, pp. 115-127
Open Access | Times Cited: 28
Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?
Lili Ding, Zhongchao Zhao, Lei Wang
Applied Energy (2022) Vol. 312, pp. 118756-118756
Closed Access | Times Cited: 22
The research landscape on the artificial intelligence: a bibliometric analysis of recent 20 years
Hui Gao, Xiu‐Hao Ding
Multimedia Tools and Applications (2022) Vol. 81, Iss. 9, pp. 12973-13001
Closed Access | Times Cited: 20
Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning
Yang Zhou, Chi Xie, Gang‐Jin Wang, et al.
Research in International Business and Finance (2022) Vol. 64, pp. 101846-101846
Closed Access | Times Cited: 20
A hybrid econometrics and machine learning based modeling of realized volatility of natural gas
Werner Kristjanpoller
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 4
A Novel Approach To Predict WTI Crude Spot Oil Price: LSTM-Based Feature Extraction With Xgboost Regressor
Ahmed İhsan Şimşek, Emre Bulut, Yunus Emre Gür, et al.
Energy (2024) Vol. 309, pp. 133102-133102
Closed Access | Times Cited: 4
Identification of important nodes in multi-layer hypergraphs based on fuzzy gravity model and node centrality distribution characteristics
Peng Wang, Guang Ling, Zhao Pei, et al.
Chaos Solitons & Fractals (2024) Vol. 188, pp. 115503-115503
Closed Access | Times Cited: 4
Early warning of regime switching in a complex financial system from a spillover network dynamic perspective
Sufang An, Xiangyun Gao, An Feng, et al.
iScience (2025) Vol. 28, Iss. 3, pp. 111924-111924
Open Access
Concatenating data-driven and reduced-physics models for smart production forecasting
Oscar I.O. Ogali, Oyinkepreye D. Orodu
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access
Artificial intelligence and dynamic pricing: a systematic literature review
Régis Chenavaz, Stanko Dimitrov
Journal of Applied Economics (2025) Vol. 28, Iss. 1
Open Access
Forecasting crude oil prices: A Gated Recurrent Unit-based nonlinear Granger Causality model
Qian Liang, Qingyuan Lin, Mengzhuo Guo, et al.
International Review of Financial Analysis (2025), pp. 104124-104124
Closed Access

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