scholarly journals Study on node importance evaluation of the high-speed passenger traffic complex network based on the Structural Hole Theory

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Xu Zhang ◽  
Bingzhi Chen
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
High Speed ◽  
Clustering Coefficient ◽  
Traffic Network ◽  
Traffic Networks ◽  
Complex Network Theory ◽  
Passenger Traffic ◽  
Structural Hole ◽  
Node Importance

AbstractComplex Network Theory can analyze the reliability of high-speed passenger traffic networks and also evaluate node importance. This paper conducts a systematic and in-depth research of importance of various nodes in the high-speed passenger traffic network so as to improve the high-speed passenger traffic network level. To study importance of network nodes can contribute to an in-depth understanding of the network structure. Therefore, the complex network is introduced and the node importance is evaluated. The characteristics of the complex network are briefly analyzed. In order to study the high-speed passenger traffic nodes, the network restraint coefficient, the network scale, the efficiency, the grade level, the partial clustering coefficient of degree and structural hole. Besides, the algorithm to calculate node importance is designed. Through analysis of the high-speed passenger network, the accuracy and practicability of the Complex Network Theory in evaluating node importance are pointed out. It is also proved that Complex Network Theory can help optimize high-speed passenger traffic networks and improve traffic efficiency.

scholarly journals Identification of Key Flight Conflict Nodes Based on Complex Network Theory

2020 ◽  
Vol 38 (2) ◽  
pp. 279-287
Author(s):  
Minggong Wu ◽  
Zekun Wang ◽  
Xusheng Gan ◽  
Guozhou Yang ◽  
Xiangxi Wen
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Air Traffic ◽  
Clustering Coefficient ◽  
Entropy Weight ◽  
Complex Network Theory ◽  
Node Importance ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Terminal Area

The air traffic density in the terminal area is high and the traffic situation is relatively complex by the development of aviation, which brings great challenges to controller. In order to understand the flight situation and provide decision basis for controllers, this paper proposes a key flight conflict nodes identification method based on complex network theory and Analytic Hierarchy Process (AHP)-entropy weight method. Firstly, an aircraft state network is established with aircraft as nodes and Airborne Collision Avoidance System (ACAS) communication relations as connecting edges. On this basis, four parameters, node degree, node weight, clustering coefficient and betweenness, are selected as evaluation indexes of node importance, and the weight of each index is determined by using AHP. And entropy weight method is introduced to revise the results. Node importance is calculated through multi-attribute decision-making method to determine key conflict aircrafts. The simulation and experiment on the artificial network and the aircraft state network of a certain day in the terminal area of Kunming Changshui Airport show that the method proposed in this paper can identify the key flight conflict nodes in the aircraft state network, allocate the selected node deployment can effectively reduce the complexity of the aircraft state network, can provide reference for air traffic control services (ATCS), and reduce the allocation difficulty of controller.

scholarly journals The Complex Network Theory-Based Urban Land-Use and Transport Interaction Studies

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Rui Ding
Keyword(s):  
Land Use ◽  
Complex Network ◽  
Network Theory ◽  
Urban Land ◽  
Urban Land Use ◽  
Urban Traffic ◽  
Traffic Network ◽  
Traffic Networks ◽  
Complex Network Theory ◽  
Urban Traffic Network

The research on complex networks offers novel insight into the analysis of complex urban systems. The objective of this article is to provide a review of complex network theory in urban land-use and transport studies to date. Some traditional integrated studies of urban land-use and traffic networks are summarized and analysed; related research gaps were proposed. Then, this paper reviewed the application of complex network theory in urban land-use and transport research and practice. It shows that the node importance identification method is critical for network protection or attack studies; the multiple centrality assessment and kernel density estimation approaches can be used to represent the intuitionistic connections of urban traffic networks and surrounding land-uses; it can be used to verify the changing trend and variation of landscape connectivity; also it can be applied to the identification of key changed land-use types in land-use cover change; the coevolution process can be treated as an integrated way to discuss the relationships between urban traffic network growth and land-use change, and the multilayer networks based analysis is a novel method to measure their interactions. This paper is essential in establishing apparent research interests and points out the further potential application of complex network theory in urban traffic network and land-use related studies.

scholarly journals Optimization of Traffic Detector Layout Based on Complex Network Theory

2020 ◽  
Vol 12 (5) ◽  
pp. 2048 ◽  
Author(s):  
Shi An ◽  
Lina Ma ◽  
Jian Wang
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Optimization Model ◽  
Numerical Experiments ◽  
Network Centrality ◽  
Traffic Network ◽  
Traffic Networks ◽  
Optimal Method ◽  
Complex Network Theory ◽  
Traffic Detector

With the recent development of traffic networks, traffic detector layout has become very complicated, due to the complexity of traffic network structures and states. Thus, this paper presents an optimal method for traffic detector layout based on network centrality using complex network theory. It mainly depends on the topology of the traffic network, and does not depend on pre-conditions (e.g., OD (Origin Destination)) traffic, path traffic, prior matrix, and so on) or consider route-choosing behavior too much. Considering the travel time, OD demand, observation demand of urban managers, dynamic characteristic of the traffic network, detector failure, and so on, an optimization model for traffic detector layout is established, which is called the Traffic Network Centrality Model (TNCM). Numerical experiments are conducted, based on data from the Sioux Falls network, which demonstrate that the model has a strong practical value. TNCM is not only helpful in reducing the traffic detector layout cost, but also improves the monitoring revenue of the traffic network in complex scenarios, which offers a promising way of thinking about the optimization of traffic detector layout schemes.

Research on the Structure of Peer-to-Peer Overlay Based on the Complex Network Theory

2012 ◽  
Vol 263-266 ◽  
pp. 1096-1099
Author(s):  
Zhi Yong Jiang
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Degree Distribution ◽  
Path Length ◽  
Small World ◽  
Peer To Peer ◽  
Clustering Coefficient ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
The Mean

Relationship between nodes in peer-to-peer overlay, currently becomes a hot topic in the field of complex network. In this paper a model of peer-to-peer overlay was purposed. And then the paper focused on figuring out the mean-shortest path length (MSPL), clustering coefficient (CC) and the degree of every node which allowed us to discover the degree distribution. The results show that the degree distribution function follows approximately power law distribution and the network possesses notable clustering and small-world properties.

scholarly journals Complex network theory, streamflow, and hydrometric monitoring system design

2015 ◽  
Vol 19 (7) ◽  
pp. 3301-3318 ◽  
Author(s):  
M. J. Halverson ◽  
S. W. Fleming
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Small World ◽  
Detection Algorithm ◽  
Clustering Coefficient ◽  
Network Stability ◽  
Meteorological Forcing ◽  
Complex Network Theory ◽  
Scale Free ◽  
Seasonal Flow

Abstract. Network theory is applied to an array of streamflow gauges located in the Coast Mountains of British Columbia (BC) and Yukon, Canada. The goal of the analysis is to assess whether insights from this branch of mathematical graph theory can be meaningfully applied to hydrometric data, and, more specifically, whether it may help guide decisions concerning stream gauge placement so that the full complexity of the regional hydrology is efficiently captured. The streamflow data, when represented as a complex network, have a global clustering coefficient and average shortest path length consistent with small-world networks, which are a class of stable and efficient networks common in nature, but the observed degree distribution did not clearly indicate a scale-free network. Stability helps ensure that the network is robust to the loss of nodes; in the context of a streamflow network, stability is interpreted as insensitivity to station removal at random. Community structure is also evident in the streamflow network. A network theoretic community detection algorithm identified separate communities, each of which appears to be defined by the combination of its median seasonal flow regime (pluvial, nival, hybrid, or glacial, which in this region in turn mainly reflects basin elevation) and geographic proximity to other communities (reflecting shared or different daily meteorological forcing). Furthermore, betweenness analyses suggest a handful of key stations which serve as bridges between communities and might be highly valued. We propose that an idealized sampling network should sample high-betweenness stations, small-membership communities which are by definition rare or undersampled relative to other communities, and index stations having large numbers of intracommunity links, while retaining some degree of redundancy to maintain network robustness.

scholarly journals Application of complex network theory in identifying critical elements of CRH2 train system

2020 ◽  
Vol 2 (1) ◽  
pp. 35-52
Author(s):  
Huiru Zhang ◽  
Limin Jia ◽  
Li Wang ◽  
Yong Qin
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
High Speed ◽  
Design Methodology ◽  
Content Type ◽  
Complex Network Theory ◽  
Critical Elements ◽  
Advantages And Disadvantages ◽  
Train Operation ◽  
Train System

Purpose Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper. Design/methodology/approach First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given. Findings Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance. Originality/value A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

scholarly journals A Novel Algorithm of Identification Theory of Complex Network for Public Transportation Network Cascading Failure

2021 ◽  
Vol 15 ◽  
pp. 236-247
Author(s):  
Xu Xu
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Public Transportation ◽  
Transportation Network ◽  
Network Evolution ◽  
Cascading Failure ◽  
Complex Network Theory ◽  
Node Importance ◽  
Public Transportation Network ◽  
Bus Network

With the development of complex network theory and the gradual application of the traffic field, the problem of cascading failure has caused great attention of researchers. This paper tries to propose a new method based on complex network theory to measure the importance of nodes in the network. Based on complex network theory, this paper first discusses the network evolution mechanism of three main contents, define the importance of nodes in the network, and the design of the network center and the evaluation of the importance of node algorithm. In the end, a critical section identification method considering the failure probability and the failure consequence is designed, and the method for calculating the node importance based on the cascading failure is proposed. Using complex network theory, a quantitative assessment of the center of public transportation network and node importance model is designed. The bus network center, for the study of node importance analysis of bus network survivability has important significance. Help guide the optimization of public transport network service. Improve transport capacity of public transportation system.

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