Research On Homogeneity Analysis Of Airport Group Based On Network Representation Learning

While driving the development of regional economic integration,the airport group should also ensure the overall efficiency of civil aviation resources,forming a pattern of unified management,differentiated development and division of labor cooperation.It is of great significance to study and analyze the degree of homogeneity of airport group for the development of airport group characterized by cooperative operation and differential development,and it can also provide decision-making basis for the subsequent route network layout of the airport group.Aiming at the problems such as single index,lack of analysis at different levels of abstraction and lack of consideration for the external navigable airports of the airport group,this paper,based on the theory and method of network,takes the Beijing Tianjin Hebei airport group as an example to analyze and explore the degree of homogeneity in the development of the airport group.The specific research work is as follows:In view of the problems of single index and single analysis level existing in the study of homogeneity of the airport group,this paper proposed a multi-level and multi-dimensional indexes of homogeneity of the airport group based on the comprehensive consideration of airport operation benefit,airport support capacity,business level and navigation situation,and constructed an analysis model of homogeneity degree of the airport group.According to the characteristics of indexes at different dimensions and levels,the homogenization calculation method based on airport attribute analysis and the homogenization calculation method based on airport network representation learning are proposed respectively.On this basis,the multilevel homogenization cascade analysis method is proposed by combining airport attributes and airport network indexes.The results show that the homogenization analysis method based on the airport attributes and the airport network is more suitable for the objective reality than the homogenization analysis method based on the closeness centrality of the complex network structure,which can better represent the degree of homogenization of the airport group.In an airport network constructed based on the airport group airport nodes and the navigable airport nodes,each airport node has unique information such as provinces,administrative regions,and geographic locations,not just an arbitrary node in the abstract network structure.Based on this consideration,the location information is regarded as the attribute information of the airport node,and combined with the attribute network representation learning method,the homogeneity analysis of the airport group based on the attribute network representation learning is proposed.In order to calculate the degree of homogeneity of the airport group,an airport node network structure feature representation vector and an airport node attribute information feature representation vector are constructed,to fuse to a unified airport node representation vector.The results of experiments on the BeijingTianjin-Hebei airport cluster related data set show that the homogeneity analysis method of the airport group based on attribute network representation learning is more accurate and credible than the above-mentioned homogeneity analysis method based on airport network representation learning.