Abstract
Ice and snow economy is an economy characterized by ice and snow, and its foundation is ice and snow resources. The ice and snow economy covers the tertiary industry of ice and snow activities, and its core power comes from ice and snow tourism, which promotes the common development of manufacturing, transportation, catering, retail, and other industries. This paper studies the low-carbon effect measurement analysis of the structural adjustment of the ice and snow industry based on artificial intelligence, which proves that the economic benefits and carbon emissions of the structural adjustment of the ice and snow industry will be greatly improved after the addition of artificial intelligence technology. For this research, a series of investigation experiments are conducted, and the ice and snow industry in Heilongjiang Province is selected for analysis. First, the important position of artificial intelligence technology in today’s information society and its practicality are fully analyzed, and then its feasibility in combination with the structural adjustment of the ice and snow industry is analyzed. Second, it analyzes the characteristics of the structural adjustment of the ice and snow industry while taking into account its requirements for measuring low-carbon effects. The mathematical model of industrial structure optimization based on low-carbon constraints is adopted in the application model of artificial intelligence technology in the adjustment of the ice and snow industry structure, and the effects of carbon emissions before and after structural adjustments in the ice and snow industry are calculated to achieve a better industrial structure adjustment plan. Experimental data shows that with the help of artificial intelligence in the process of structural adjustment of the ice and snow industry, the average income of residents has increased by nearly 7%, and the transformation of the ice and snow industry’s contribution to the reduction of carbon emissions has rapidly increased to 12.24%.
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