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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:

Forecasting the crude oil prices with an EMD-ISBM-FNN model
Tianhui Fang, Chunling Zheng, Donghua Wang
Energy (2022) Vol. 263, pp. 125407-125407
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Prediction of Complex Stock Market Data Using an Improved Hybrid EMD-LSTM Model
Muhammad Ali, Dost Muhammad Khan, Huda M. Alshanbari, et al.
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1429-1429
Open Access | Times Cited: 71
Multistep short-term wind power forecasting model based on secondary decomposition, the kernel principal component analysis, an enhanced arithmetic optimization algorithm, and error correction
Guolian Hou, Junjie Wang, Yuzhen Fan
Energy (2023) Vol. 286, pp. 129640-129640
Closed Access | Times Cited: 38
Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis
Jiahao Zhang, Xiaodan Chen, Wei Yu, et al.
International Review of Financial Analysis (2023) Vol. 88, pp. 102659-102659
Closed Access | Times Cited: 27
Incorporating Russo-Ukrainian war in Brent crude oil price forecasting: A comparative analysis of ARIMA, TARMA and ENNReg models
Sagiru Mati, Magdalena Rădulescu, Najia Saqib, et al.
Heliyon (2023) Vol. 9, Iss. 11, pp. e21439-e21439
Open Access | Times Cited: 18
Point and interval wind speed forecasting of multivariate time series based on dual-layer LSTM
Haipeng Zhang, Jianzhou Wang, Yuansheng Qian, et al.
Energy (2024) Vol. 294, pp. 130875-130875
Closed Access | Times Cited: 8
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: 6
An enhanced interval-valued decomposition integration model for stock price prediction based on comprehensive feature extraction and optimized deep learning
Jujie Wang, Jing Liu, Weiyi Jiang
Expert Systems with Applications (2023) Vol. 243, pp. 122891-122891
Closed Access | Times Cited: 15
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
Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration
Yun Bai, Shuyun Deng, Ziqiang Pu, et al.
Energy (2024) Vol. 305, pp. 132338-132338
Closed Access | Times Cited: 5
Enhanced complete ensemble EMD with superior noise handling capabilities: A robust signal decomposition method for power systems analysis
Manuel Soto Calvo, Han Soo Lee
Engineering Reports (2024) Vol. 6, Iss. 11
Open Access | Times Cited: 4
Non-destructive testing of composite materials with ultrasonic array based on EMD-ATRM
Jincheng Pan, Shaobo Li, Dongchao Lv, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-34
Closed Access
A hybrid system with optimized decomposition on random deep learning model for crude oil futures forecasting
Jie Wang, Ying Zhang
Expert Systems with Applications (2025), pp. 126706-126706
Closed Access
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
EMD-CPO-GRU-based Transformer Oil Temperature Prediction
Pengbo Han
(2025) Vol. 2, Iss. 2, pp. 69-76
Closed Access
A hybrid model for multistep-ahead significant wave height prediction using an innovative decomposition–reconstruction framework and E-GRU
Mie Wang, Feixiang Ying
Applied Ocean Research (2023) Vol. 140, pp. 103752-103752
Closed Access | Times Cited: 10
Decomposition prediction fractional-order PID reinforcement learning for short-term smart generation control of integrated energy systems
Linfei Yin, Da Zheng
Applied Energy (2023) Vol. 355, pp. 122246-122246
Closed Access | Times Cited: 9
A Novel Hybrid Prediction Model of Air Quality Index Based on Variational Modal Decomposition and CEEMDAN-SE-GRU
Chaoli Tang, Ziyu Wang, Yuanyuan Wei, et al.
Process Safety and Environmental Protection (2024) Vol. 191, pp. 2572-2588
Closed Access | Times Cited: 3
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
Investigation on spatter characteristics of liquid phase and life span of submerged lance in the top-blown smelting process using hydraulic modelling
Kai Yang, Bo Yu, Wuliang Yin, et al.
Advanced Powder Technology (2024) Vol. 35, Iss. 6, pp. 104492-104492
Closed Access | Times Cited: 2
Hybrid model for robust and accurate forecasting building electricity demand combining physical and data-driven methods
Xianzhou Dong, W. Guo, Cheng Zhou, et al.
Energy (2024), pp. 133309-133309
Closed Access | Times Cited: 2
Household Energy Consumption Forecasting based on Adaptive Signal Decomposition Enhanced iTransformer Network
Jian Liu, Fan Yang, Ke Yan, et al.
Energy and Buildings (2024) Vol. 324, pp. 114894-114894
Closed Access | Times Cited: 2
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: 6
Portfolios with return and volatility prediction for the energy stock market
Yilin Ma, Yudong Wang, Weizhong Wang, et al.
Energy (2023) Vol. 270, pp. 126958-126958
Closed Access | Times Cited: 5
Relevance of hybrid artificial intelligence for improving the forecasting accuracy of natural resource prices
Mei Li, Rida Waheed, Derviş Kırıkkaleli, et al.
Geoscience Frontiers (2023) Vol. 15, Iss. 3, pp. 101670-101670
Open Access | Times Cited: 5
Crude oil price prediction using temporal fusion transformer model
Kaijian He, Linyuan Zheng, Qian Yang, et al.
Procedia Computer Science (2023) Vol. 221, pp. 927-932
Open Access | Times Cited: 4
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