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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:

Ensemble forecasting for product futures prices using variational mode decomposition and artificial neural networks
Weiping Liu, Chengzhu Wang, Yonggang Li, et al.
Chaos Solitons & Fractals (2021) Vol. 146, pp. 110822-110822
Closed Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

Runoff Forecasting using Convolutional Neural Networks and optimized Bi-directional Long Short-term Memory
Tunhua Wu, Zhaocai Wang, Yuan Hu, et al.
Water Resources Management (2023) Vol. 37, Iss. 2, pp. 937-953
Closed Access | Times Cited: 76
The impact of Russia–Ukraine war on crude oil prices: an EMC framework
Qi Zhang, Yi Hu, Jianbin Jiao, et al.
Humanities and Social Sciences Communications (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 27
A novel hybrid model based on deep learning and error correction for crude oil futures prices forecast
Tunhua Wu, Jinghan Dong, Zhaocai Wang, et al.
Resources Policy (2023) Vol. 83, pp. 103602-103602
Closed Access | Times Cited: 36
A novel crude oil prices forecasting model based on secondary decomposition
Guohui Li, Shibo Yin, Hong Yang
Energy (2022) Vol. 257, pp. 124684-124684
Closed Access | Times Cited: 34
A hybrid approach to forecasting futures prices with simultaneous consideration of optimality in ensemble feature selection and advanced artificial intelligence
Indranil Ghosh, Tamal Datta Chaudhuri, Esteban Alfaro, et al.
Technological Forecasting and Social Change (2022) Vol. 181, pp. 121757-121757
Open Access | Times Cited: 27
Enhanced forecasting method for realized volatility of energy futures prices: A secondary decomposition-based deep learning model
Hao Gong, H. Y. Xing, Qianwen Wang
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110321-110321
Closed Access
Optimal forecast combination based on PSO-CS approach for daily agricultural future prices forecasting
Liling Zeng, Liwen Ling, Dabin Zhang, et al.
Applied Soft Computing (2022) Vol. 132, pp. 109833-109833
Closed Access | Times Cited: 24
An ensemble self-learning framework combined with dynamic model selection and divide-conquer strategies for carbon emissions trading price forecasting
Rui Yang, Hui Liu, Yanfei Li
Chaos Solitons & Fractals (2023) Vol. 173, pp. 113692-113692
Closed Access | Times Cited: 14
Short-term power load forecasting system based on rough set, information granule and multi-objective optimization
Jianzhou Wang, Kang Wang, Zhiwu Li, et al.
Applied Soft Computing (2023) Vol. 146, pp. 110692-110692
Closed Access | Times Cited: 14
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
Crude Oil Price Forecasting Model Based on Neural Networks and Error Correction
Guangji Zheng, Ye Li, Yu Xia
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1055-1055
Open Access
Multi-step-ahead copper price forecasting using a two-phase architecture based on an improved LSTM with novel input strategy and error correction
Hongyuan Luo, Deyun Wang, Jinhua Cheng, et al.
Resources Policy (2022) Vol. 79, pp. 102962-102962
Closed Access | Times Cited: 21
Cluster-based industrial KPIs forecasting considering the periodicity and holiday effect using LSTM network and MSVR
Ziyuan Wang, Can Zhou, Yishun Liu, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 101916-101916
Closed Access | Times Cited: 12
A fuzzy-based cascade ensemble model for improving extreme wind speeds prediction
C. Peláez‐Rodríguez, Jorge Pérez‐Aracil, L. Prieto-Godino, et al.
Journal of Wind Engineering and Industrial Aerodynamics (2023) Vol. 240, pp. 105507-105507
Open Access | Times Cited: 12
Text‐based soybean futures price forecasting: A two‐stage deep learning approach
Wuyue An, Lin Wang, Yu‐Rong Zeng
Journal of Forecasting (2022) Vol. 42, Iss. 2, pp. 312-330
Closed Access | Times Cited: 16
Artificial Intelligence Techniques in Economic Analysis
Robertas Damaševičius
Economic Analysis Letters (2023)
Open Access | Times Cited: 9
A Combined Prediction Model for Hog Futures Prices Based on WOA‐LightGBM‐CEEMDAN
Xiang Wang, Shen Gao, Yibin Guo, et al.
Complexity (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 15
A non-ferrous metal price ensemble prediction system based on innovative combined kernel extreme learning machine and chaos theory
Honggang Guo, Jianzhou Wang, Zhiwu Li, et al.
Resources Policy (2022) Vol. 79, pp. 102975-102975
Closed Access | Times Cited: 12
A novel three-stage hybrid learning paradigm based on a multi-decomposition strategy, optimized relevance vector machine, and error correction for multi-step forecasting of precious metal prices
Jianguo Zhou, Zhongtian Xu
Resources Policy (2022) Vol. 80, pp. 103148-103148
Closed Access | Times Cited: 12
Predicting Natural Gas Prices Based on a Novel Hybrid Model with Variational Mode Decomposition
Qin Lu, Jingwen Liao, Kechi Chen, et al.
Computational Economics (2023) Vol. 63, Iss. 2, pp. 639-678
Closed Access | Times Cited: 7
A Multi-Factor Selection and Fusion Method through the CNN-LSTM Network for Dynamic Price Forecasting
Yishun Liu, Chunhua Yang, Keke Huang, et al.
Mathematics (2023) Vol. 11, Iss. 5, pp. 1132-1132
Open Access | Times Cited: 7
A systematic literature review on price forecasting models in construction industry
Mingxue Ma, Vivian W.Y. Tam, Khoa N. Le, et al.
International Journal of Construction Management (2023) Vol. 24, Iss. 11, pp. 1191-1200
Open Access | Times Cited: 7
A Hybrid Model for Carbon Price Forecasting Based on Improved Feature Extraction and Non-Linear Integration
Yingjie Zhu, Yongfa Chen, Qiuling Hua, et al.
Mathematics (2024) Vol. 12, Iss. 10, pp. 1428-1428
Open Access | Times Cited: 2
An Innovative Deep Learning Futures Price Prediction Method with Fast and Strong Generalization and High-Accuracy Research
Lin Huo, Y. H. Xie, Jianbo Li
Applied Sciences (2024) Vol. 14, Iss. 13, pp. 5602-5602
Open Access | Times Cited: 2
Digital twin for zinc roaster furnace based on knowledge-guided variable-mass thermodynamics: Modeling and application
Chengzhu Wang, Zhijie Wang, Keke Huang, et al.
Process Safety and Environmental Protection (2023) Vol. 173, pp. 39-50
Closed Access | Times Cited: 6
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