Research on the application of a combined model in carbon emission prediction

Liu Rui, Cai Feijun
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Abstract

Nowadays, the prediction accuracy of carbon emissions is required to be improved, a combination model for prediction is proposed. First, calculate the carbon emissions according to the carbon emission conversion formula of petrochemical energy consumption, then use the trend moving average method to pre-process the calculated carbon emissions, and finally combine the pre-processed data with the grey linear regression model to realize the prediction of future carbon emissions. The experimental results show that the prediction accuracy of using traditional linear regression model and GM (1,1) is low, while using the grey linear regression model is good, but it is still lower than using the combined model proposed.
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组合模型在碳排放预测中的应用研究
为了提高碳排放的预测精度,提出了一种组合预测模型。首先根据石化能耗碳排放换算公式计算出碳排放量,然后利用趋势移动平均法对计算出的碳排放量进行预处理,最后将预处理后的数据与灰色线性回归模型相结合,实现对未来碳排放量的预测。实验结果表明,使用传统线性回归模型和GM(1,1)的预测精度较低,而使用灰色线性回归模型的预测精度较好,但仍低于使用所提出的组合模型。
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