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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 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: 158

Showing 1-25 of 158 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: 875
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: 238
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: 222
Do green bonds and economic policy uncertainty matter for carbon price? New insights from a TVP-VAR framework
Houjian Li, Qingman Li, Xinya Huang, et al.
International Review of Financial Analysis (2023) Vol. 86, pp. 102502-102502
Closed Access | Times Cited: 72
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: 71
Forecasting carbon price in China using a novel hybrid model based on secondary decomposition, multi-complexity and error correction
Hong Yang, Xiaodie Yang, Guohui Li
Journal of Cleaner Production (2023) Vol. 401, pp. 136701-136701
Closed Access | Times Cited: 46
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: 31
Examining the linkage between economic policy uncertainty, coal price, and carbon pricing in China: Evidence from pilot carbon markets
Jiqiang Wang, Peng‐Fei Dai, Xihui Haviour Chen, et al.
Journal of Environmental Management (2024) Vol. 352, pp. 120003-120003
Closed Access | Times Cited: 23
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: 138
A new secondary decomposition ensemble learning approach for carbon price forecasting
Hongtao Li, Feng Jin, Shaolong Sun, et al.
Knowledge-Based Systems (2020) Vol. 214, pp. 106686-106686
Closed Access | Times Cited: 124
Multistep-ahead forecasting of coal prices using a hybrid deep learning model
Zakaria Alameer, Ahmed Fathalla, Kenli Li, et al.
Resources Policy (2020) Vol. 65, pp. 101588-101588
Closed Access | Times Cited: 118
Valued forest carbon sinks: How much emissions abatement costs could be reduced in China
Boqiang Lin, Jiamin Ge
Journal of Cleaner Production (2019) Vol. 224, pp. 455-464
Closed Access | Times Cited: 101
Point and interval forecasting for carbon price based on an improved analysis-forecast system
Tian Cheng-shi, Hao Yan
Applied Mathematical Modelling (2019) Vol. 79, pp. 126-144
Open Access | Times Cited: 99
A combination forecasting model based on hybrid interval multi-scale decomposition: Application to interval-valued carbon price forecasting
Jinpei Liu, Piao Wang, Huayou Chen, et al.
Expert Systems with Applications (2021) Vol. 191, pp. 116267-116267
Closed Access | Times Cited: 81
Interaction among China carbon emission trading markets: Nonlinear Granger causality and time-varying effect
Lili Zhao, Fenghua Wen, Xiong Wang
Energy Economics (2020) Vol. 91, pp. 104901-104901
Closed Access | Times Cited: 80
What drive carbon price dynamics in China?
Fenghua Wen, Haocen Zhao, Lili Zhao, et al.
International Review of Financial Analysis (2021) Vol. 79, pp. 101999-101999
Closed Access | Times Cited: 80
A new hybrid optimization ensemble learning approach for carbon price forecasting
Shaolong Sun, Feng Jin, Hongtao Li, et al.
Applied Mathematical Modelling (2021) Vol. 97, pp. 182-205
Closed Access | Times Cited: 66
A new carbon price prediction model
Guohui Li, Zhiyuan Ning, Hong Yang, et al.
Energy (2021) Vol. 239, pp. 122324-122324
Closed Access | Times Cited: 59
Carbon price prediction considering climate change: A text-based framework
Qiwei Xie, Jingjing Hao, Jingyu Li, et al.
Economic Analysis and Policy (2022) Vol. 74, pp. 382-401
Closed Access | Times Cited: 56
Carbon Pricing Mechanism for the Energy Industry: A Bibliometric Study of Optimal Pricing Policies
Yuanyuan Guo, Xunjie Gou, Zeshui Xu, et al.
Acta Montanistica Slovaca (2022), Iss. 27, pp. 49-69
Open Access | Times Cited: 46
A novel carbon price prediction model based on optimized least square support vector machine combining characteristic-scale decomposition and phase space reconstruction
Wei Sun, Junjian Zhang
Energy (2022) Vol. 253, pp. 124167-124167
Closed Access | Times Cited: 45
A novel carbon price combination forecasting approach based on multi-source information fusion and hybrid multi-scale decomposition
Piao Wang, Jinpei Liu, Zhifu Tao, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 114, pp. 105172-105172
Closed Access | Times Cited: 42
An ensemble dynamic self-learning model for multiscale carbon price forecasting
Wen Zhang, Zhibin Wu, Xiao‐Jun Zeng, et al.
Energy (2022) Vol. 263, pp. 125820-125820
Open Access | Times Cited: 40
Carbon price combination prediction model based on improved variational mode decomposition
Guohui Li, Caifeng Zheng, Hong Yang
Energy Reports (2022) Vol. 8, pp. 1644-1664
Open Access | Times Cited: 39
An enhanced hybrid model based on multiple influencing factors and divide-conquer strategy for carbon price prediction
Jujie Wang, Zhenzhen Zhuang, Dongming Gao
Omega (2023) Vol. 120, pp. 102922-102922
Closed Access | Times Cited: 37
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