Research On The Structure Of Chinese High-speed Railway Network Community Based On Complex Network Theory

Complex network theory has been applied to many different fields.The application in high-speed railway network is mainly reflected in the use of complex network theory indicators to analyze its characteristics,but there are not many studies on the community structure in high-speed railway networks.By studying the community structure in the high-speed railway network,we can better grasp the structural characteristics of the highspeed railway network and provide a new reference for optimizing the layout of the highspeed railway network.First,by using the data of high-speed rail lines and high-speed rail train times,three network models of high-speed rail geographic network,train flow network and service network are constructed,and their characteristics are analyzed.The results show that in the high-speed rail geographic network from 2014 to 2020,both the urban degree value and the clustering coefficient have increased,indicating that the number of high-speed rail lines between cities has gradually increased and the degree of connection between adjacent cities has been strengthened.The average path length is large,and the inter-city accessibility level is low.The betweenness centrality of urban nodes is severely polarized,reflecting the imbalance in the structure of the geographic network.In the high-speed railway traffic network,the city degree value has increased,and the connectivity between cities has increased.The clustering coefficient has decreased,and the closeness of connections between adjacent cities has decreased.The average path length has increased,indicating that the level of network accessibility between cities has decreased.The betweenness centrality polarization of urban nodes is relatively reduced,and the difference in connectivity between cities becomes smaller.Secondly,five community discovery algorithms: GN algorithm,Newman fast algorithm,Louvain algorithm,LPA algorithm and Walktrap algorithm are used to divide the high-speed railway geographic network and high-speed railway service network.Research shows that the characteristics of community structure in the two network models are more significant.Finally,through the analysis of the community structure in the two models,it is found that the communities in the high-speed railway geographic network are mainly distributed along the high-speed rail lines,and are affected by factors such as geographic location and administrative division.The number of associations in the high-speed railway service network is significantly less than that in the high-speed railway geographic network,which shows that the connections between cities in the high-speed railway service network are closer.From the perspective of the distribution of cities based on multiple indicators,the most important city nodes in the community are mainly provincial capital cities or high-speed rail hub cities.The range of associations does not match the range of urban agglomerations.The same urban agglomeration is divided into different associations with a large proportion,and the allocation of high-speed rail resources within the urban agglomeration is not balanced.Figure 26;Table 21;Reference 57...