A Novel Muilti-layer Associate Rules Mining Algorithm for Relations between Carbon Emission Futures Price and European Economy

Abstract

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.