Nonlinear Relationship and Its Evolutionary Trace between Node Degree and Average Path Length of China Aviation Network Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the relationship between the node degree and the average path length of China aviation network in 1988,1994,2001,2008 and 2015 was studied.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network.On the basis of the statistical data,the node average path length of China aviation network in 1988,1994,2001,2008 and 2015 was calculated.Through regression analysis,it was found that the node degree had a logarithmic relationship with the average length of node path,and the two parameters of the logarithmic relationship had linear evolutionary trace.Key word:China aviation network,complex network,node degree,average length of node path,logarithmic relationship,evolutionary trace.

Probability Distribution of China Aviation Network Average Degree of Edge Vertices and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the average degrees of edge vertices in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the average degree of edge vertices had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.

Nonlinear Relationship and Its Evolutionary Trace between Average Degree and Average Path Length of Edge Vertices of China Aviation Network Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the relationship between the average degree and the average path length of edge vertices of China aviation network in 1988,1994,2001,2008 and 2015 was studied.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network.On the basis of the statistical data,the average degree and average path length of edge vertices of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Through regression analysis,it was found that the average degree had a logarithmic relationship with the average path length of edge vertices and the two parameters of the logarithmic relationship had linear evolutionary trace.

Probability Distribution of Ratio of China Aviation Network Edge Vertices Degree and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of ratio of China aviation network edge vertices degree were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the ratio of edge vertices degree in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the ratio of edge vertices degree had linear probability distribution and the two parameters of the probability distribution had linear evolution trace.

Probability Distribution of Arithmetic Average of China Aviation Network Edge Vertices Nearest Neighbor Average Degree Value and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average degree values of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the arithmetic averages of edge vertices nearest neighbor average degree values of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the arithmetic average of edge vertices nearest neighbor average degree values had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.

Nonlinear Relationship and Its Evolutionary Trace between Node Degree and Nearest Neighbor Average Degree of China Aviation Network Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network, the relationship between the node degree and the nearest neighbor average degree and its evolution trace of China aviation network in 1988, 1994, 2001, 2008 and 2015 were studied. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network. According to the statistical data, the node nearest neighbor average degree of China aviation network in 1988, 1994, 2001, 2008 and 2015 was calculated. Through regression analysis, it was found that the node degree had a negative exponential relationship with the nearest neighbor average degree, and the two parameters of the negative exponential relationship had linear evolution trace.

Probability Distribution of China Aviation Network Nearest Neighbor Average Degree and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of node nearest neighbor average degree of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the nearest neighbor average degrees of nodes in China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the nearest neighbor average degree had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.

Comparing of Aviation Network Structure of Mid-south,Northwest and Southwest of China Based on Hierarchical Index Model

In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and improve its structure,hierarchical index model of regional aviation network was established through dividing the aviation network into layers to research its structure characters.Data matrixes were defined to record the basic state of regional aviation network.Index matrixes were constructed to describe the quantitative features of regional aviation network.On the basis of these indexes,several structure indexes of all layers of aviation network were calculated to show the structure features of aviation network,such as ratio of passenger volume within the region with across the region,share rate of passenger volume among layers,ratio of average number of airline for each airport,ratio of average passenger volume for each airline and ratio of airline rate.According to the statistical data,similar structure of share rate of passenger volume among layers and average passenger volume for each airline in their regional aviation network was found after calculating.But on the side of ratio of passenger volume within the region with across the region,ratio of average number of airlines for each airport and ratio of airline rate were different.

Community Detection in Aviation Network Based on K-means and Complex Network

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.

Probability Distribution and Their Non-linear Relationship between Node Degree and Clustering Coefficient of Aviation Network of China Based on Complex Network

In order to reveal the complex network feature of aviation network of China,probability distribution of node degree and clustering coefficient of aviation network of China was researched according to statistics data of civil aviation of China.It was verified that node degree had power function probability distribution.Clustering coefficient of nodes with exponential function probability distribution was discovered.It was found that node degree and clustering coefficient had single peak nonlinear relationship.At the left side of the peak,there is no certain relationship between them.At the right side of the peak,clustering coefficient became smaller with the rise of node degree and there was negative exponential function relationship between them by regression analysis.

Probability Distribution of Edge in Adjacent Matrix of Aviation Network of China and Algorithm of Searching Non-overlap Community Structure Based on Complex Network

In order to discover the probability distribution feature of edge in aviation network adjacent matrix of China and on the basis of this feature to establish an algorithm of searching non-overlap community structure in network to reveal the inner principle of complex network with the feature of small world in aspect of adjacent matrix and community structure,aviation network adjacent matrix of China was transformed according to the node rank and the matrix was arranged on the basis of ascending node rank with the center point as original point.Adjacent probability from the original point to extension around in approximate area was calculated.Through fitting probability distribution curve,power function of probability distribution of edge in adjacent matrix arranged by ascending node rank was found.According to the feature of adjacent probability distribution,deleting step by step with node rank ascending algorithm was set up to search non-overlap community structure in network and the flow chart of algorithm was given.A non-overlap community structure with 10 different scale communities in aviation network of China was found by the computer program written on the basis of this algorithm.

The study of driving force concerning aviation network

With the continuous development of our country＇ s economy, social economy expands to the globe increasingly.The amount of imports and exports increases to a new high, which leads to the rapid development of the aviation transportation. This article is written by constructing theoretical models of aviation network, analyzing the relative influencing factors, analyzing the instances and obtaining the final conclusion.

Probability Distribution of Average Length of Node Path and Its Evolution Trace of Aviation Network of China Based on Complex Network

In order to reveal the complex network feature and its evolution principle of aviation network of China,probability distribution and its evolution trace of average length of node path of aviation network of China were researched according to statistics data in years 1988,1994,2001,2008 and 2015 of civil aviation of China.Floyd algorithm to calculate the path length between any two nodes of network was applied and average length of node path of aviation network was obtained according to this algorithm.It was discovered that average length of node path to other nodes had normal distribution function in each year.At meantime,the location parameter and scale parameter of normal distribution function had linear evolution trace.Airline rate was an index to describe the density of airline.It was found that average length of node path of aviation network of China evolved synchronously with airline rate and they had linear relationship.

Structure Evolution of China Aviation Network Based on Hierarchical Model

The annual passenger volume of airport reflected its passenger transport scale and the role in aviation network.The airports in whole country were divided into three layers:first layer airports,second layer airports and third layer airports.The airlines from the first layer airports consisted the first layer aviation network.The airlines from the second layer airports consisted the second layer aviation network.The airlines from the third layer airports consisted the third layer aviation network.The structure and function of different layer aviation network had significant differences.These differences were shown in the number of airlines,average number of airlines of each airport,annual passenger volume of airport and average passenger volume of each airline.National aviation network hierarchical model was constructed to describe the whole country aviation network.The matrix was built to describe the airline number,annual passenger volume,average number of airlines,average passenger volume of each airport and airline rate of aviation network.The index of national aviation network structure was constructed to show the ratio of index between different aviation network layer to describe the aviation network structure.The structure index was built to illustrate the macrostructural features of national aviation network.The statistics data in year 1988,1994,2001,2008 and 2015 of China aviation network were analyzed and basic data matrixes,basic index matrixes and structure index matrixes were calculated.The trend of ratio of corresponding index between the first layer and the second layer showed the change of basic structure of China aviation network.At meantime,the tendency of ratio of corresponding index between the third layer and the second layer also showed the change of basic structure.The trend of network general structure index illustrated that the large scaled new airports and airlines construction had significant influence on the national aviation network structure.

Design and analysis of a network coding algorithm for ad hoc networks

Network coding is proved to have advantages in both wireline and wireless networks. Especially, appropriate network coding schemes are programmed for underlined networks. Considering the feature of strong node mobility in aviation communication networks, a hop-by-hop network coding algorithm based on ad hoc networks was proposed. Compared with COPE-like network coding algorithms, the proposed algorithm does not require overhearing from other nodes, which meets confidentiality requirements of aviation communication networks. Meanwhile, it does save resource consumption and promise less processing delay. To analyze the performance of the network coding algorithm in scalable networks with different traffic models, a typical network was built in a network simulator, through which receiving accuracy rate and receiving delay were both examined.The simulation results indicate that, by virtue of network coding, the proposed algorithm works well and improves performance significantly. More specifically, it has better performance in enhancing receiving accuracy rate and reducing receiving delay, as compared with any of the traditional networks without coding. It was applied to both symmetric and asymmetric traffic flows and, in particular, it achieves much better performance when the network scale becomes larger. Therefore, this algorithm has great potentials in large-scale multi-hop aviation communication networks.

Analysis on the driving forces of different airports and routes

There has been a great deal of research on the driving force of aviation network.Moreover, the research methods and perspectives are also varied.This article mainly studies the driving force of aviation network,the influencing factors of main driving force are analyzed.The driving force analysis of different airport and route is carried out respectively.The results can better reveal the connection mechanism of solid routes.Because the sample space of the hub airport and the trunk airport is too small,the conclusions are not sufficiently illustrative,therefore, this article studies only the branch airports.The conclusions are compared with the results of the comprehensive analysis,and we see if the conclusions are the same or similar.

Simulation Analysis of the Effect of Relaxation Time on Flight Delays Propagation

Relaxation time of flights is one of the main factors that affect the diffusion of flight delays, but the specific relationship between them is ambiguous.？Gaining a clear idea of their relationship conduces to the control of flight delays.？Through the establishment of the aviation network model and simulation analysis of the effect of relaxation time on delay spread, it can be found that the relaxation time is inversely proportional to the total delay time and the number of airports that have been delayed due to the delay spread, and there is no evident linear relationship between the relaxation time and the average delay time.？This demonstrates that increasing the relaxation time properly can reduce the propagation of flight delays and improve the punctuality rate of flights.