With the increasing number of airports and the expansion of their scale, the aviation network has become complex and hierarchical. In order to investigate the complex network characteristics of aviation networks, this paper constructs a Chinese aviation network model and carries out related research based on complex network theory and K-means algorithm. Initially, the P-space model is employed to construct the Chinese aviation network model. Then, complex network indicators such as degree, clustering coefficient, average path length, betweenness and coreness are selected to investigate the complex characteristics and hierarchical features of aviation networks and explore their causes. Secondly, using K-means clustering algorithm, five values are obtained as the initial clustering parameter K values for each of the aviation network hierarchies classified according to five complex network indicators. Meanwhile, clustering simulation experiments are conducted to obtain the visual clustering results of Chinese aviation network nodes under different K values, as well as silhouette coefficients for evaluating the clustering effect of each indicator in order to obtain the hierarchical classification of aviation networks under different indicators. Finally, the silhouette coefficient is optimal when the K value is 4. Thus, the clustering results of the four layers of the aviation network can be obtained. According to the experimental results, the complex network association discovery method combined with K-means algorithm has better applicability and simplicity, while the accuracy is improved.
To enhance the accuracy of performance analysis of regional airline network, this study applies complex network theory and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to investigate the topology of regional airline network, constructs node importance index system, and clusters 161 airport nodes of regional airline network. Besides, entropy power method and approximating ideal solution method (TOPSIS) is applied to comprehensively evaluate the importance of airport nodes and complete the classification of nodes and identification of key points; adopt network efficiency, maximum connectivity subgraph and network connectivity as vulnerability measurement indexes, and observe the changes of vulnerability indexes of key nodes under deliberate attacks and 137 nodes under random attacks. The results demonstrate that the decreasing trend of the maximum connectivity subgraph indicator is slower and the decreasing trend of the network efficiency and connectivity indicators is faster when the critical nodes of the regional airline network are deliberately attacked. Besides, the decreasing trend of the network efficiency indicator is faster and the decreasing trend of the maximum connectivity subgraph indicator is slower when the nodes of four different categories are randomly attacked. Finally, it is proposed to identify and focus on protecting critical nodes in order to better improve the security level of regional airline system.
Combined with the actual situation of smart airport construction, five listed airports in China are used as research objects, and based on the Driving Force-Pressure-State-Impact-Response (DPSIR) conceptual model, 24 indicators were selected to form the evaluation system. The Analytic Hierarchy Process (AHP) method and entropy weight method were used to assign comprehensive weights to the indicators, and then, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method was introduced to evaluate the level of intelligence, combined with the coupling coordination model to analyze the relationship between the two subsystems, by introducing the obstacle model to diagnose and analyze the influencing factors; finally, based on the analysis results, optimization suggestions are provided for the airport intelligence level. The results show that the intelligence level of each airport is between high (IV) and average (II). The pairwise coupling degree of each subsystem is higher than 0.91 and presents a benign coupling. The airport intelligence level is mainly hindered by the proportion of nonaviation revenue, the average travel time of passengers, and the regional fiscal revenue growth rate. The research results are of great significance to the construction of smart airport and the development of regional economy and transportation.
The insufficiency of the development of airport land-side transportation has limited the radiation range of airport passengers to a certain extent. As a way to realize the connection of land and air transportation, airport land-side transportation has become an important order parameter to promote the expansion of the radiation range of airport passengers. Using the basic concepts of coupling and coupling degree, this paper constructs a coupling system of airport land-side traffic-airport passenger radiation range. Focusing on the two major subsystems of land-side traffic and radiation range, a corresponding evaluation index system is established. Meanwhile, the major airports in Shaanxi Province and Anhui Province are taken as examples to realize the quantitative development process of the coupling development process of airport land-side traffic and airport passenger radiation range. According to the results, in the early stage of airport development, passengers with aviation needs drive the development of airport land-side traffic, and for those with the gradual improvement of land-side traffic, the radiation range of airport passengers is also reversely expanded. Besides, the the two can develop in the direction of benign coupling.
“Transportation service is convenient, comfortable, economical and efficient” is one of the purposes of “ The Program of Building National Strength in Transportation”. The high-capacity and high-efficiency fast passenger and freight services provided by the aviation industry meet this need. Civil aviation industry is not only a social service industry, but also an industry closely related to the economic situation. At present, there is a lack of research on the evaluation of socioeconomic adaptability of civil aviation development. From aspects of civil aviation development and economy and society, this paper constructs the index system of socioeconomic adaptability of civil aviation development. And then in this paper, the method of DEA is used to evaluate its adaptability, and the year with better adaptability is found. At the same time, this paper also briefly analyzes the fluctuation of civil aviation passenger transport market, which lays a theoretical foundation for the subsequent development planning of civil aviation, and promotes the high-quality development of civil aviation to a certain extent. And it will achieve the goal of “people’s aviation for the people”, and then promote the process of building a powerful transportation country.
Based on the study of the influence mechanism of airports on regional economic development, this paper empirically analyzes the interaction between small and medium-sized airports and regional economic development by using the data of Mianyang Nanjiao airport from 2002 to 2017, in order to provide measurement methods and theoretical support for local governments to encourage and promote the development of local airports. In the part of empirical analysis, firstly, this paper constructs the air transport scale index system of small and medium-sized airports and the evaluation index system of regional economic development. Then, the entropy method is selected to select the key factors of the airport, so as to obtain the airport transportation capacity equivalent, and the principal component analysis method is used to extract the high load index of the regional economic system. Finally, this paper establishes the SVAR model of airport transportation capacity and regional economic relationship, carries out structural impulse response and variance decomposition analysis, draws the conclusion that small and medium-sized airports have a positive impact on regional economic development, but not significant, and analyzes the reasons.
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