Optimization of New Energy Vehicle Industry Structure Based on Optimization Link Prediction Similarity Algorithm and CGE

Optimization of New Energy Vehicle Industry Structure Based on Optimization Link Prediction Similarity Algorithm and CGE

Blog Article

In light of the growing global concerns over energy and climate change, new energy vehicles are confronted with both Tube Cutting Guide opportunities and challenges posed by industrial structural transformation.To foster the optimization of the new energy vehicle industry structure while considering environmental impact, this paper first uses an improved link prediction algorithm to construct an industrial structure optimization model.Then, a computable general equilibrium model is used to explore the effect of a carbon tax on the new energy vehicle industry.

The proposed model had the best area under the curve on the Karate network and FWFW network, which were 90.64% and 65.05%.

In the Jazz network, the prediction accuracy was 92.65%.The prediction accuracy of the proposed model for the “Yangtze River Delta” and “Beijing Tianjin Hebei” regions was 86.

37% and 85.62%.With the gradual rise of carbon tax rates and emission reductions, the demand for electricity, coal, and oil in the new energy vehicle manufacturing industry was gradually decreasing.

The gross domestic product and total output of the manufacturing industry were gradually decreasing, and the total investment was gradually increasing.This result demonstrates the application Food Service:Commercial Kitchen Equipment:Food Preparation Equipment:Other Commercial Food Prep effect of the proposed industrial structure optimization model and indicates that carbon tax collection will have an impact on carbon emissions and energy demand.This research will help promote the optimization of the new energy vehicle industry structure and promote the sustainable growth of the national economy.