基于支持向量回归机的河北省能源消费碳排放预测

doi:10.11799/ce201708047

Abstract

Abstract: This paper analyzes the advantage of support vector regression (SVR) in the projection of carbon emission and establishes the model of projection of carbon emission based on SVR. The model with good learning and generalization ability is established through using the data of Hebei’s carbon emissions and influence factors from the year 1990 to 2013 as samples to train and test and then predicts Hebei’s carbon emissions from the year 2014 to 2020. The results show that Hebei’s carbon emissions have an increasing tendency from the year 1990 to 2020 as a whole, increasing stably and less during the period of 1990-2000 and 2010-2020 but faster from 2000 to 2010; there would be also adding up to 4441.76 tons carbon emissions in Hebei between 2014 and 2020 and keeping a stable increase rate about 3%. Finally according to the data of projection, this paper provides some suggestions which are beneficial to the Hebei’s carbon reduction.

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The SVR-based projection of Hebei’s carbon emissions resulting from energy consumption

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