Analysis On Route Network Structure Of Small And Medium-sized Airports

As an important part of China’s airline network,small and medium-sized airports are the basis of the popularization of air travel.However,under the background of the rapid development of China’s air transportation industry,the development of small and medium-sized airports is relatively lagging behind,and there is a large market to be expanded.Therefore,it is necessary to analyze the structure of the current route network of small and medium-sized airports in order to meet the requirements of the high-quality development of civil aviation for the scientific construction of route network.Taking the route network of small and medium-sized airports in the summer and autumn season of 2019 as the research object,we first analyze the network structure characteristics and distribution characteristics combined with complex network index.Meanwhile,we analyze the route connection mechanism of small and medium-sized airports from the perspective of multiple factors by using the link prediction theory and evaluation method.The coupling proximity algorithm with the best prediction result is used to predict the new routes of small and medium-sized airports in the future,and the prediction results are tested.The results show that:(1)In terms of the structure and connection characteristics of the route network of small and medium-sized airports,the average connection scale of the route of small and medium-sized airports is one sixth of that of large airports.Its intermediate order scale distribution is at the bottom of the network,and its transit capacity is weak,but its average cluster coefficient in the overall network is at the same level as that of the whole,so it has strong agglomeration in the overall network.After analyzing the indexes weighted by passenger volume and distance,it is found that the connection scale of small and medium-sized airports after weighting is still at the mid-low level.The small and medium-sized airports with high intermediate number do not mean that they have the characteristics of high passenger volume or long distance.The order scale distribution of small and medium-sized airports with cluster coefficient greater than 0.6 has certain agglomeration,and the weighted edge intermediate number obeys power-law distribution,extremely many routes have small weighted edge intermediate number and are not of strong importance,the eastern coastal areas lack weighted high intermediate number routes.In addition,small and medium-sized airports with different throughput scales tend to connect with large airports,and their internal connection scale levels are similar and small.Small and medium-sized airports with low intermediate number tend to connect with small and medium-sized airports with high intermediate number.(2)The research on the connection mechanism of the route network of small and medium-sized airports shows that the takeoff and landing sorties have the best prediction effect among the exogenous attributes.The prediction accuracy of the four endogenous factor indexes is higher than that of the exogenous attribute indexes except takeoff and landing sorties.Among them,the prediction accuracy of the local path index is the highest,which means that mining the structural information inside the network is more conducive to predicting the network connection.Coupling internal and external factors or attributes can improve the accuracy of route connection prediction.The prediction effect of coupling algorithm is better than that of single index,and LP index plays a leading role in coupling algorithm.Based on the comparison between the prediction results of the coupling algorithm and the new routes in the future,it is found that the predicted routes are mainly concentrated in the eastern region,and most small and medium-sized airports will still choose large airports for connection.The predicted routes account for more than one third of the actual new routes in the next two years.The structural stability brought by network evolution has a great impact on the prediction effect of new routes.