碳排放期货价格与欧洲经济关系的多层关联规则挖掘算法

Bing He, Wei Xiao, Yuanyuan Hu, Pingping Xiang
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引用次数: 0

摘要

采用数据挖掘中的多维关联规则算法,定量分析了碳排放期货价格与人口与就业、消费、国内生产、对外贸易四个方面影响欧洲经济的十大因素之间的影响关系。结果表明,在人口和就业因素方面,失业率与CEFP呈负相关。在消费方面,CEFP与消费水平呈正相关。在国内生产总值方面,CEFP价格与国内生产总值、增加值总值和经济总量呈正相关。利用数据挖掘技术,定量分析CEFP与影响因素的关联度,为相关部门投资CEFP提供科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Muilti-layer Associate Rules Mining Algorithm for Relations between Carbon Emission Futures Price and European Economy
The multi-dimensional association rule algorithm in data mining was used to quantitatively analyze the influence relationship between carbon emission futures price (CEFP) and ten influencing Europe economic factors in four aspects: population and employment, consumption, domestic product, foreign trade. The results showed that, in terms of population and employment factors, unemployment was negatively correlated with CEFP. In terms of consumption, CEFP is positively correlated with consumption level. In terms of domestic product, CEFP price is positively correlated with gross domestic product, gross added value and total economy. Data mining technology is used to quantitatively analyze the correlation degree between CEFP and influencing factors, in order to provide scientific basis for the relevant departments to invest CEFP.
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