Research On Optimizing The Peak Route Of Carbon Emission In China's Heavy Industries Based On Integrated Intelligent Algorithms

As the pillar of China's economic development in the past decades,heavy industry has developed vigorously in accordance with the traditional economic development mode.Heavy industry has also produced huge carbon emissions,which has become an important part of China's carbon emissions.In order to further deepen the sustainable development model of "Lucid waters and lush mountains are invaluable assets.",the government proposed in the 13 th Five-Year Plan of Work on Controlling Greenhouse Gas Emissions,striving to achieve the first peak of carbon emissions in some heavy industries around 2020,and achieving positive results in the low-carbon transformation of energy system,industrial system and consumption field.In view of the lack of literature on heavy industry and peak path optimization,it is necessary and novel to study the peak path optimization of carbon emissions in China's heavy industry.The optimization of carbon emission peak path of China's heavy industry is not only an effective way to promote high-quality development of China's economy in the new era and alleviate global climate change,but also a beneficial choice to explore a new road to industrialization and realize a new model of industrial development.From the perspective of management science and engineering,this paper takes China's heavy industry and its sub-industries as the research object.Firstly,it introduces the carbon emission measurement methods and industry scope.Then it analyses the energy consumption level and carbon emission level of China's heavy industry from 1990 to 2016.Seven factors affecting carbon emissions are selected from the perspectives of population structure,economic development and energy consumption.Secondly,this paper integrates the theory of intelligent algorithms such as neural network,particle swarm optimization and genetic algorithm,and constructs the research model of carbon emission peak path of heavy industry in China.The error test results show that the model used in this paper has higher accuracy and practicability than other similar models.According to the predicted results of government policies and authoritative bodies,nine scenarios of conservative,benchmark and intensified development were set up to forecast the carbon emission peak path and peak situation of heavy industry and its sub-industries in China in 2017-2050.Finally,through the analysis of the simulation results,the optimum carbon emission peak path of China's heavy industry and sub-industries is obtained.The optimum peak time is 2025.The carbon emission of power industry is the largest in sub-industries,and the carbon emission of machinery manufacturing industry is the smallest.In addition,this paper puts forward optimization strategies and suggestion parameters of carbon emission peak path from population structure,economic development,energy consumption,macro-control and other aspects.Specifically,on the basis of carrying out capacity-free plan,it implements the control of total energy consumption,keeps the population growing at medium speed,enhances the urbanization rate at high speed,develops the economy with high quality,and strives to adjust and optimize the energy consumption structure.At the same time,we set the optimum peak value target for seven factors,which can provide methodological support and data reference for China's heavy industry and sub-industries to achieve the goal of peak as soon as possible.