Analysis of energy consumption and carbon emission prediction of shanghai municipality based on attention mechanism improved CNN-BiGRU and LMDI
In light of the growing significance of sustainable development and ecological environmental protection on a global and Chinese scale,Shanghai,as the economic hub of China,occupies a pivotal position in the transition of energy consumption patterns and the reduction of carbon emissions.This paper collates energy consumption data for Shanghai from 2001 to 2020.It employs the LMDI and an optimized CNN-BiGRU neural network model based on the attention mechanism to provide an in-depth analysis and prediction of Shanghai's energy consumption data over the years.A variety of factors,including economic,social and technological development,are taken into account in the scenario analysis,which predicts the carbon emissions of Shanghai from 2021 to 2035.The analysis also puts forward suggestions for energy-saving and emission reduction measures in Shanghai,with the aim of promoting optimization.Furthermore,the optimization of Shanghai's energy structure,enhancement of energy utilization efficiency,reduction of carbon emissions and facilitation of the transformation of Shanghai's economy to a green and low-carbon status will contribute to the realization of China's and the world's carbon-neutral goals.