Cited by 307Stock Market Forecasting MethodsForecasting Techniques and ApplicationsEnergy Load and Power Forecasting

Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression

Open access
Zhu, Bangzhu, Han, Dong, Wang, Ping, Wu, Zhanchi, Zhang, Tao, Wei, Yi-Ming·2017·Applied Energy

Integrity signals

Registry

Crossref · 10.1016/j.apenergy.2017.01.076

Cites

47 of 47 references verified0 citation errors · 0 not checkable

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  • ML can be used to analyze prices within cap-and-trade markets, for example by predicting prices via supervised learning or analyzing the main drivers of prices via hierarchical clustering.

    “ML can be used to analyze prices within these markets, for example by predicting prices via supervised learning [769,834,890,892] or analyzing the main drivers of prices via hierarchical clustering [891].”

    From Tackling climate change with machine learning (2023) · cites this paper as [890]

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Authors
Zhu, B., Han, D., Wang, P., Wu, Z., Zhang, T., & Wei, Y.-M.
Affiliations
  • Jinan University (CN)
  • University of Birmingham (GB)
  • Beijing Institute of Technology (CN)
Corresponding author
  • Zhu, Bangzhu
  • Wu, Zhanchi
Venue
Applied Energy
Publisher
Elsevier BV
Published
2017-04
Volume
191
Pages
521-530
ISSN
0306-2619 (ISSN-L)
OpenAlex
W2586354609
Cited by
307
References
47
Citations by year
2026: 22 · 2025: 46 · 2024: 43 · 2023: 45 · 2022: 39 · 2021: 29 · 2020: 25 · 2019: 32 · 2018: 23 · 2017: 3
FWCI
20.11
Type
journal article
Language
en
Open access
Locations
  • Applied Energy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
  • Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by-nc-nd)
Funders
  • National Natural Science Foundation of China (NSFC) (71473180, 71201010, 71303174, 71303076, 71673083)
  • National Philosophy and Social Science Foundation of China (14AZD068, 15ZDA054, 16ZZD049)
  • Guangdong Young Zhujiang Scholar
  • Natural Science Foundation for Distinguished Young Talents of Guangdong (2014A030306031)
  • Soft Science Foundation of Guangdong (2014A070703062)
  • Social Science Foundation of Guangdong (GD14XYJ21)
  • Distinguished Young Teachers of Guangdong ([2014]145, [2013]246)
  • High-level Personnel Project of Guangdong
  • Guangdong Key Base of Humanities
  • Social Science—Enterprise Development Research Institute
  • Institute of Resource, Environment and Sustainable Development Research
  • Guangzhou key Base of Humanities and Social Science—Centre for Low Carbon Economic Research
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
Keywords
carbon price forecasting, empirical mode decomposition, particle swarm optimization, carbon futures, EU Emissions Trading System

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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