Prediction of Regional Carbon Emission Path Based on CEE Adaptive Linkage Model

In the context of international carbon peak and carbon neutrality, it is difficult to transform the energy structure based on fossil energy such as coal. At the same time, the use of consumer-side terminal energy also has a huge impact on overall carbon emissions. The reduction of carbon emissions involves many complex variables. There is an urgent need to build a regional carbon emission prediction and feedback mechanism. This paper proposes an intelligent prediction model based on economic, energy and carbon linkage, establishes the linkage relationship between carbon emissions and social and economic development, builds the underlying logic from the perspective of social demand, predicts regional emissions, and simultaneously forms a feedback mechanism for carbon reduction and emission reduction. When carbon emission targets are clear, neural algorithm iterations can be used to find energy transition and industry optimization paths. The actual calculation of the energy economy in a certain region verifies the rationality of the algorithm in this paper.