河南科技大学学报（自然科学版）2024，Vol.45Issue(1)：51-61,11.DOI:10.15926/j.cnki.issn1672-6871.2024.01.007
融合新闻影响力衰减的碳价格多元分解集成预测
A Multivariate Decomposition Ensemble Prediction Method for Carbon Prices Incorporating News Influence Exponential Attenuation
摘要
Abstract
The news covers information closely related to carbon prices,including policies,economics,and energy.Its impact on carbon prices is time-sensitive.To quantify the degree of news influence attenuation,this paper proposes a method for calculating attenuated news influence based on word frequency statistics and exponential decay,which extracts features from news data.The decay influence of news more accurately reflects the extent of its influence on carbon prices.In order to improve prediction accuracy,this paper constructs a multivariate decomposition-ensemble prediction model of carbon prices incorporating news influence exponential attenuation.It applies noise-assisted multivariate empirical mode decomposition method to decompose the data into several subcomponents.Then the subcomponents are reconstructed based on sample entropy.Finally,machine learning methods are applied to predict the subcomponents,which are aggregated to obtain the prediction results.A case study of empirical analysis is conducted using carbon prices of Hubei province.The results show that the news influence exponential attenuation can effectively portray the correlation between news and carbon prices.The proposed multivariate decomposition-ensemble model shows excellent and stable prediction performance.关键词
碳价格预测/新闻影响力/指数衰减/噪声辅助多元经验模态分解/样本熵Key words
carbon price forecasting/news influence/exponential attenuation/NAMEMD分类
管理科学引用本文复制引用
张大斌,黄均杰,凌立文,胡焕玲..融合新闻影响力衰减的碳价格多元分解集成预测[J].河南科技大学学报（自然科学版）,2024,45(1):51-61,11.基金项目
国家自然科学基金项目(71971089,72001083) （71971089,72001083）
广东省自然科学基金项目(2022A1515011612) （2022A1515011612）
