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An ensemble dynamic self-learning model for multiscale carbon price forecasting · Study

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ArticleAn ensemble dynamic self-learning model for multiscale carbon price forecasting

Wen Zhang2022

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Articlegreen2022

An ensemble dynamic self-learning model for multiscale carbon price forecasting

Wen Zhang · Zhibin Wu · Xiao‐Jun Zeng · Changhui Zhu

61 citations·0/0 files stored·Energy

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Stock Market Forecasting Methods Forecasting Techniques and Applications Energy Load and Power Forecasting

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References

2010An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect 2022Carbon price forecasting based on CEEMDAN and LSTM 2018A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting 2019Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors 2018A multiscale analysis for carbon price drivers 2018Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS 2020Does weather, or energy prices, affect carbon prices?2018Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm

Cited by

2024Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks 2024Framework for multivariate carbon price forecasting: A novel hybrid model 2023SimVGNets: Similarity-Based Visibility Graph Networks for Carbon Price Forecasting 2023A novel interval-valued carbon price analysis and forecasting system based on multi-objective ensemble strategy for carbon trading market

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Details

Year2022

Typearticle

Published2022-10-22

VenueEnergy

ISSN-L0360-5442

Languageen

Citations61

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1016/j.energy.2022.125820

openalex_workW4307085545

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