In order to improve the congestion of the evacuation plan and further improve the evacuation efficiency, this paper proposes the priority Pareto partial order relation and the vector pheromone routing method based on the priority Pareto partial order relation. Numerical experiments show that compared with the hierarchical multiobjective evacuation path optimization algorithm based on the hierarchical network, the fragmented multiobjective evacuation path optimization algorithm proposed in this paper effectively improves the evacuation efficiency of the evacuation plan and the convergence of the noninferior plan set. However, the congestion condition of the noninferior evacuation plan obtained by the fragmented multiobjective evacuation route optimization algorithm is worse than the congestion condition of the noninferior evacuation plan obtained by the hierarchical multiobjective evacuation route optimization algorithm. The multiple factors that affect the routing process considered in the probability transfer function used in the traditional ant colony algorithm routing method must be independent of each other. However, in actual route selection, multiple factors that affect route selection are not necessarily independent of each other. In order to fully consider the various factors that affect the routing, this paper adopts the vector pheromone routing method based on the traditional Pareto partial order relationship instead of the traditional ant colony algorithm. The model mainly improves the original pheromone distribution and volatilization coefficient of the ant colony, speeds up the convergence speed and accuracy of the algorithm, and obtains ideal candidate solutions. The method is applied to the location of sports facilities and has achieved good results. The experimental results show that the improved ant colony algorithm model designed in this paper is suitable for solving the problem of urban sports facilities location in large-scale space.
Under the background of “Internet + Ice and Snow Tourism,” the tourism industry has ushered in new development opportunities and external challenges. “Internet + tourism” breeds a new huge tourism market. This new market consists of netizens + purchasing power + purchasing desire. This paper mainly selects the integration of mobile ice and snow tourism and tourism and leisure industry as the main research subject, focusing on the in-depth study of the future development trend of the integration of ice and snow tourism and leisure industry and the mobile Internet industry. The analysis found that the tourism industry in the ice and snow area mainly has the following problems: the division of functional areas is not clear, there is a large gap between service innovation capabilities and industrial demand, and the level of industrial informatization is inconsistent with development goals and the lack of market service credit. On the basis of combining tourism Internet service platform and big data marketing experience, creatively propose to create a new development pattern of “one network, three places and one platform” for ice and snow tourism, promote the “Three New Coverage Projects” of the tourism network, and build a new cross-business cooperation mechanism of “Internet + Tourism”; rely on Internet marketing and publicity measures to enhance the development of tourism service integrity and other countermeasures; use Internet thinking to solve the problems of tourism industry development; and provide suggestions for the innovative development of the tourism industry in the ice and snow regions and the entire autonomous region. The implementation of these countermeasures predicts that the local economy will increase by at least 51.28%, so the development of the “Internet + ice and snow tourism” type industry in combination with the actual situation is not waiting.
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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