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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 carbon price using empirical mode decomposition and evolutionary least squares support vector regression
Bangzhu Zhu, Dong Han, Ping Wang, et al.
Applied Energy (2017) Vol. 191, pp. 521-530
Open Access | Times Cited: 242

Showing 1-25 of 242 citing articles:

A review of deep learning for renewable energy forecasting
Huaizhi Wang, Zhenxing Lei, Xian Zhang, et al.
Energy Conversion and Management (2019) Vol. 198, pp. 111799-111799
Closed Access | Times Cited: 861
Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 2, pp. 1-96
Open Access | Times Cited: 458
Machine learning in energy economics and finance: A review
Hamed Ghoddusi, Germán G. Creamer, Nima Rafizadeh
Energy Economics (2019) Vol. 81, pp. 709-727
Closed Access | Times Cited: 340
Carbon price forecasting based on CEEMDAN and LSTM
Feite Zhou, Zhehao Huang, Changhong Zhang
Applied Energy (2022) Vol. 311, pp. 118601-118601
Closed Access | Times Cited: 249
Carbon trading volume and price forecasting in China using multiple machine learning models
Hongfang Lü, Xin Ma, Kun Huang, et al.
Journal of Cleaner Production (2019) Vol. 249, pp. 119386-119386
Closed Access | Times Cited: 235
A carbon price prediction model based on secondary decomposition algorithm and optimized back propagation neural network
Wei Sun, Chenchen Huang
Journal of Cleaner Production (2019) Vol. 243, pp. 118671-118671
Closed Access | Times Cited: 221
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
What will China's carbon emission trading market affect with only electricity sector involvement? A CGE based study
Boqiang Lin, Zhijie Jia
Energy Economics (2018) Vol. 78, pp. 301-311
Closed Access | Times Cited: 218
China's carbon emissions trading and stock returns
Fenghua Wen, Nan Wu, Xu Gong
Energy Economics (2019) Vol. 86, pp. 104627-104627
Closed Access | Times Cited: 216
A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting
Bangzhu Zhu, Shunxin Ye, Ping Wang, et al.
Energy Economics (2018) Vol. 70, pp. 143-157
Open Access | Times Cited: 183
Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 165
Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors
Meng Han, Lili Ding, Xin Zhao, et al.
Energy (2019) Vol. 171, pp. 69-76
Open Access | Times Cited: 153
An innovative random forest-based nonlinear ensemble paradigm of improved feature extraction and deep learning for carbon price forecasting
Jujie Wang, Xin Sun, Qian Cheng, et al.
The Science of The Total Environment (2020) Vol. 762, pp. 143099-143099
Closed Access | Times Cited: 141
Analysis and forecast of China's energy consumption structure
Sheng Zeng, Bin Su, Minglong Zhang, et al.
Energy Policy (2021) Vol. 159, pp. 112630-112630
Closed Access | Times Cited: 124
Predicting China's carbon price based on a multi-scale integrated model
Shaozhou Qi, Shihan Cheng, Xiujie Tan, et al.
Applied Energy (2022) Vol. 324, pp. 119784-119784
Closed Access | Times Cited: 69
Financial Time Series Forecasting with the Deep Learning Ensemble Model
Kaijian He, Qian Yang, Lei Ji, et al.
Mathematics (2023) Vol. 11, Iss. 4, pp. 1054-1054
Open Access | Times Cited: 54
A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China
Hanxiao Shi, Anlei Wei, Xiaozhen Xu, et al.
Journal of Environmental Management (2024) Vol. 352, pp. 120131-120131
Closed Access | Times Cited: 47
Forecasting carbon price with attention mechanism and bidirectional long short-term memory network
Chaoyong Qin, Dongling Qin, Qiuxian Jiang, et al.
Energy (2024) Vol. 299, pp. 131410-131410
Closed Access | Times Cited: 26
Enhancing carbon price point-interval multi-step-ahead prediction using a hybrid framework of autoformer and extreme learning machine with multi-factors
Baoli Wang, Zhaocai Wang, Zhiyuan Yao
Expert Systems with Applications (2025), pp. 126467-126467
Closed Access | Times Cited: 4
A Novel Ensemble Learning Framework Based on News Sentiment Enhancement and Multi-objective Optimizer for Carbon Price Forecasting
Yujie Chen, Mingyao Jin, Zheyu Zhou, et al.
Computational Economics (2025)
Closed Access | Times Cited: 3
Deep belief network based ensemble approach for cooling load forecasting of air-conditioning system
Guoyin Fu
Energy (2018) Vol. 148, pp. 269-282
Closed Access | Times Cited: 159
Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm
Wei Sun, Chongchong Zhang
Applied Energy (2018) Vol. 231, pp. 1354-1371
Closed Access | Times Cited: 158
Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS
Xin Zhao, Meng Han, Lili Ding, et al.
Applied Energy (2018) Vol. 216, pp. 132-141
Open Access | Times Cited: 141
A hybrid model using signal processing technology, econometric models and neural network for carbon spot price forecasting
Jinliang Zhang, Dezhi Li, Yu Hao, et al.
Journal of Cleaner Production (2018) Vol. 204, pp. 958-964
Closed Access | Times Cited: 139
A hybrid framework for carbon trading price forecasting: The role of multiple influence factor
Hao Yan, Tian Cheng-shi
Journal of Cleaner Production (2020) Vol. 262, pp. 120378-120378
Closed Access | Times Cited: 135
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