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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 mode-characteristic-based decomposition ensemble model for nuclear energy consumption forecasting
Ling Tang, Shuai Wang, Kaijian He, et al.
Annals of Operations Research (2014) Vol. 234, Iss. 1, pp. 111-132
Closed Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

A Comparative Study of Empirical Mode Decomposition-Based Short-Term Wind Speed Forecasting Methods
Ye Ren, Ponnuthurai Nagaratnam Suganthan, Narasimalu Srikanth
IEEE Transactions on Sustainable Energy (2014) Vol. 6, Iss. 1, pp. 236-244
Closed Access | Times Cited: 303
Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network
Yu‐Rong Zeng, Yi Zeng, Beomjin Choi, et al.
Energy (2017) Vol. 127, pp. 381-396
Closed Access | Times Cited: 228
A hybrid model for carbon price forecasting using GARCH and long short-term memory network
Yumeng Huang, Xingyu Dai, Qunwei Wang, et al.
Applied Energy (2021) Vol. 285, pp. 116485-116485
Closed Access | Times Cited: 219
Online big data-driven oil consumption forecasting with Google trends
Lean Yu, Yaqing Zhao, Ling Tang, et al.
International Journal of Forecasting (2018) Vol. 35, Iss. 1, pp. 213-223
Closed Access | Times Cited: 210
A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting
Lean Yu, Zishu Wang, Ling Tang
Applied Energy (2015) Vol. 156, pp. 251-267
Closed Access | Times Cited: 182
Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture
Peijun Zheng, Heng Zhou, Jiang Liu, et al.
Applied Energy (2023) Vol. 349, pp. 121607-121607
Closed Access | Times Cited: 48
Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach
Lean Yu, Jingjing Li, Ling Tang, et al.
Energy Economics (2015) Vol. 51, pp. 300-311
Closed Access | Times Cited: 156
A SVR–ANN combined model based on ensemble EMD for rainfall prediction
Yu Xiang, Ling Gou, Lihua He, et al.
Applied Soft Computing (2018) Vol. 73, pp. 874-883
Closed Access | Times Cited: 142
A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting
Ling Tang, Wei Dai, Lean Yu, et al.
International Journal of Information Technology & Decision Making (2014) Vol. 14, Iss. 01, pp. 141-169
Closed Access | Times Cited: 132
A compressed sensing based AI learning paradigm for crude oil price forecasting
Lean Yu, Yang Zhao, Ling Tang
Energy Economics (2014) Vol. 46, pp. 236-245
Closed Access | Times Cited: 121
A hybrid VMD–BiGRU model for rubber futures time series forecasting
Qing Zhu, Fan Zhang, Shan Liu, et al.
Applied Soft Computing (2019) Vol. 84, pp. 105739-105739
Closed Access | Times Cited: 108
The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm
Manrui Jiang, Lifen Jia, Zhensong Chen, et al.
Annals of Operations Research (2020) Vol. 309, Iss. 2, pp. 553-585
Closed Access | Times Cited: 87
Application of a novel structure-adaptative grey model with adjustable time power item for nuclear energy consumption forecasting
Song Ding, Ruojin Li, Shu Wu, et al.
Applied Energy (2021) Vol. 298, pp. 117114-117114
Closed Access | Times Cited: 86
Economic growth and environmental degradation: evidence from the US case environmental Kuznets curve hypothesis with application of decomposition
Serdar Ongan, Cem Işık, Dilek Özdemir
Journal of Environmental Economics and Policy (2020) Vol. 10, Iss. 1, pp. 14-21
Closed Access | Times Cited: 82
An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting
Dongchuan Yang, Ju’e Guo, Shaolong Sun, et al.
Applied Energy (2021) Vol. 306, pp. 117992-117992
Closed Access | Times Cited: 74
A novel fractional time-delayed grey Bernoulli forecasting model and its application for the energy production and consumption prediction
Yong Wang, Xinbo He, Lei Zhang, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 110, pp. 104683-104683
Closed Access | Times Cited: 56
Hybrid intelligent framework for carbon price prediction using improved variational mode decomposition and optimal extreme learning machine
Jujie Wang, Quan Cui, Maolin He
Chaos Solitons & Fractals (2022) Vol. 156, pp. 111783-111783
Closed Access | Times Cited: 47
Short-term load forecasting with an improved dynamic decomposition-reconstruction-ensemble approach
Dongchuan Yang, Ju’e Guo, Yanzhao Li, et al.
Energy (2022) Vol. 263, pp. 125609-125609
Closed Access | Times Cited: 37
A dynamic clustering ensemble learning approach for crude oil price forecasting
Jiaxin Yuan, Jianping Li, Jun Hao
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106408-106408
Closed Access | Times Cited: 22
Forecasting smart home electricity consumption using VMD-Bi-GRU
Ismael Jrhilifa, Hamid Ouadi, Abdelilah Jilbab, et al.
Energy Efficiency (2024) Vol. 17, Iss. 4
Closed Access | Times Cited: 12
LSSVR ensemble learning with uncertain parameters for crude oil price forecasting
Lean Yu, Huijuan Xu, Ling Tang
Applied Soft Computing (2016) Vol. 56, pp. 692-701
Closed Access | Times Cited: 74
A New Hybrid VMD-ICSS-BiGRU Approach for Gold Futures Price Forecasting and Algorithmic Trading
Yuze Li, Shouyang Wang, Yunjie Wei, et al.
IEEE Transactions on Computational Social Systems (2021) Vol. 8, Iss. 6, pp. 1357-1368
Closed Access | Times Cited: 50
McVCsB: A new hybrid deep learning network for stock index prediction
Chenhao Cui, Peiwan Wang, Yong Li, et al.
Expert Systems with Applications (2023) Vol. 232, pp. 120902-120902
Closed Access | Times Cited: 18
Ensemble Forecasting for Complex Time Series Using Sparse Representation and Neural Networks
Lean Yu, Yang Zhao, Ling Tang
Journal of Forecasting (2016) Vol. 36, Iss. 2, pp. 122-138
Closed Access | Times Cited: 57
A hybrid grid-GA-based LSSVR learning paradigm for crude oil price forecasting
Lean Yu, Wei Dai, Ling Tang, et al.
Neural Computing and Applications (2015) Vol. 27, Iss. 8, pp. 2193-2215
Closed Access | Times Cited: 55
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