The prediction of carbon emission in all provinces of China with the K-means cluster based Logistic model

With the K-means clustering and Logistic model, we forecasted the carbon emissions in 30 provinces and autonomous regions in China from 2014 to 2023 based on the data of 30 provinces from 2005 to 2013. First, 5 indicators were selected, which include GDP, urbanization rate, the proportion of the second industry, the energy efficiency and the carbon emission intensity. Secondly, K-means cluster analysis method was used to divide the carbon emission into 5 types. Finally, the Logistic model of carbon emissions growth was built, to predict the carbon emissions these procinces from 2014 to 2023. It was found that the carbon emission of China from 2014 to 2023 is increasing continuously.