Prediction Of Carbon Tax In Beijing,Henan And Guangxi Based On BP Neural Network

The carbon tax is levied on excessive carbon dioxide emissions,the purpose is to protect the environment and slow global warming.It is for the excessive amount of carbon dioxide emissions.Developed countries have levied carbon tax for a long time,and the effect is very obvious.As China has transformed from extensive economic growth to intensive,cost-effective economic growth.Especially the needs of the development of low-carbon economy.The imposition of carbon tax has become an important goal of china's the 13 th Five-Year development plan.However,due to the information asymmetry,which is leading to the dispute over the effective of china's carbon tax,and the institution construction lags behind the developed countries seriously.At present,there are few researches on visual stimulation of carbon tax in china.Therefore,it is necessary to use BP Neural Network to calculate the weight and threshold of Chinese carbon tax is,and study the effects of carbon tax levied in typical areas.The following is the main work of this paper.Firstly,researches are based on carbon tax levy theory,as well as BP Neural Network theory and method.Secondly,analysis of the principles,steps and feasibility of applying BP Neural Network to predict the carbon tax in China.It also designs BP Neural Network structure,training function,and builds prediction model.Thirdly,realization of carbon tax forecasting model in China,selects carbon emission intensity(carbon emissions/regional GDP)and urban residents' bear to carbon tax(carbon tax/urban residents' disposable income).It is used for dividing the carbon tax area and analyzing of carbon tax data source characteristics.Fourth,the effect of carbon tax collection and carbon tax forecast based on BP neural network,show virtual simulation results,Among the seven provinces on Beijing,Shanghai,Anhui,Zhejiang,Hunan,Guangxi,Henan.the eastern developed areas,take Beijing as a typical example;the middle less developed areas is typical of Henan province;the western development region is typical of the Guangxi Zhuang Autonomous Region.And the carbon tax levy for the next few years for further analysis of the forecast.the relationship between the variation of GDP and the area of urban residents per-capita disposable income of carbon tax is studied by BP Neural Network.Construct the prediction model of virtual simulation.The research shows that there is no direct relation between the introduction of carbon tax and regional GDP change,and urban residents' average disposable income change.Therefore,the construction of carbon tax system should focus on strengthening the informationization construction,reducing information communication barriers,and improving carbon tax management,monitoring and service.