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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 decomposition ensemble based deep learning approach for crude oil price forecasting
He Jiang, Weiqiang Hu, Ling Xiao, et al.
Resources Policy (2022) Vol. 78, pp. 102855-102855
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Price forecasting through neural networks for crude oil, heating oil, and natural gas
Bingzi Jin, Xiaojie Xu
Deleted Journal (2024) Vol. 1, pp. 100001-100001
Open Access | Times Cited: 115
A novel hybrid model for crude oil price forecasting based on MEEMD and Mix-KELM
Jingjing Li, Zhanjiang Hong, Chengyuan Zhang, et al.
Expert Systems with Applications (2024) Vol. 246, pp. 123104-123104
Closed Access | Times Cited: 11
Deep learning systems for forecasting the prices of crude oil and precious metals
Parisa Foroutan, Salim Lahmiri
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 5
A Study of Optimization in Deep Neural Networks for Regression
Chieh-Huang Chen, Jung-Pin Lai, Yu-Ming Chang, et al.
Electronics (2023) Vol. 12, Iss. 14, pp. 3071-3071
Open Access | Times Cited: 15
Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models
Sourav Kumar Purohit, Sibarama Panigrahi
Information Sciences (2023) Vol. 658, pp. 120021-120021
Closed Access | Times Cited: 15
Dynamic impacts of online investor sentiment on international crude oil prices
Lu‐Tao Zhao, Yue-Yue Xing, Qiu-Rong Zhao, et al.
Resources Policy (2023) Vol. 82, pp. 103506-103506
Closed Access | Times Cited: 13
A robust time-varying weight combined model for crude oil price forecasting
Longlong Liu, Suyu Zhou, Jie Qian, et al.
Energy (2024) Vol. 299, pp. 131352-131352
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
China’s Energy Stock Price Index Prediction Based on VECM–BiLSTM Model
Bingchun Liu, Zhang Xia, Yuan Gao, et al.
Energies (2025) Vol. 18, Iss. 5, pp. 1242-1242
Open Access
A new hybrid model for multi-step WTI futures price forecasting based on self-attention mechanism and spatial–temporal graph neural network
Geya Zhao, Minggao Xue, Li Cheng
Resources Policy (2023) Vol. 85, pp. 103956-103956
Closed Access | Times Cited: 11
Fortify the investment performance of crude oil market by integrating sentiment analysis and an interval-based trading strategy
Kun Yang, Zishu Cheng, Mingchen Li, et al.
Applied Energy (2023) Vol. 353, pp. 122102-122102
Closed Access | Times Cited: 10
Machine learning Brent crude oil price forecasts
Bingzi Jin, Xiaojie Xu
Innovation and Emerging Technologies (2024) Vol. 11
Closed Access | Times Cited: 3
Can real-time investor sentiment help predict the high-frequency stock returns? Evidence from a mixed-frequency-rolling decomposition forecasting method
Yi Cai, Zhenpeng Tang, Ying Chen
The North American Journal of Economics and Finance (2024) Vol. 72, pp. 102147-102147
Closed Access | Times Cited: 2
Geopolitical risk and crude oil price predictability: Novel decomposition ensemble approach based ternary interval number series
Y. T. Li, Yiyan Chen, Hooi Hooi Lean
Resources Policy (2024) Vol. 92, pp. 104966-104966
Closed Access | Times Cited: 2
Crude Oil Prices Forecast Based on Mixed-Frequency Deep Learning Approach and Intelligent Optimization Algorithm
Wanbo Lu, Zhaojie Huang
Entropy (2024) Vol. 26, Iss. 5, pp. 358-358
Open Access | Times Cited: 2
Oil Sector and Sentiment Analysis—A Review
Marcus Vinicius Bastos dos Santos, Fernando Morgado‐Dias, Thiago Christiano Silva
Energies (2023) Vol. 16, Iss. 12, pp. 4824-4824
Open Access | Times Cited: 5
A secondary decomposition-ensemble methodology for forecasting natural gas prices using multisource data
Gang Xie, Fuxin Jiang, Chengyuan Zhang
Resources Policy (2023) Vol. 85, pp. 104059-104059
Closed Access | Times Cited: 5
Bionic-inspired oil price prediction: Auditory multi-feature collaboration network
Han Wu, Yan Liang, Xiao‐Zhi Gao, et al.
Expert Systems with Applications (2023) Vol. 244, pp. 122971-122971
Closed Access | Times Cited: 5
A novel secondary decomposition method for forecasting crude oil price with twitter sentiment
Jieyi Li, Shuangyue Qian, Ling Li, et al.
Energy (2023) Vol. 290, pp. 129954-129954
Closed Access | Times Cited: 5
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
A multiscale time-series decomposition learning for crude oil price forecasting
Jinghua Tan, Z Li, Chuanhui Zhang, et al.
Energy Economics (2024) Vol. 136, pp. 107733-107733
Closed Access | Times Cited: 1
A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention
Zisheng Ouyang, Min Lü, Zhongzhe Ouyang, et al.
Energy Economics (2024) Vol. 138, pp. 107851-107851
Closed Access | Times Cited: 1
Using Deep Learning, Optuna, and Digital Images to Identify Necrotizing Fasciitis
M. Tsai, Chung-Hui Lin, Jung-Pin Lai, et al.
Electronics (2024) Vol. 13, Iss. 22, pp. 4421-4421
Open Access | Times Cited: 1
Crude Oil Spot Price Forecasting Using Ivanov-Based LASSO Vector Autoregression
Yishan Ding, Dongwei He, Jun Wu, et al.
Complexity (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 3
Intelligent Crude Oil Price Probability Forecasting: Deep Learning Models and Industry Applications
Liang Shen, Yukun Bao, Najmul Hasan, et al.
(2024)
Closed Access
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