Evaluation of Airline Alliance Route Network Efficiency Based on Complex Network

2019 ◽  
Author(s):  
Jiajia Shao ◽  
Wendong Yang ◽  
Hai Jiang
Keyword(s):  
Complex Network ◽  
Network Efficiency ◽  
Route Network ◽  
Airline Alliance

Analyses of the response of a complex weighted network to nodes removal strategies considering links weight: The case of the Beijing urban road system

2018 ◽  
Vol 32 (05) ◽  
pp. 1850067 ◽  
Author(s):  
Michele Bellingeri ◽  
Zhe-Ming Lu ◽  
Davide Cassi ◽  
Francesco Scotognella
Keyword(s):  
Complex Network ◽  
Real World ◽  
Road Traffic ◽  
Network Efficiency ◽  
Weighted Network ◽  
Node Importance ◽  
Connected Cluster ◽  
Binary Network ◽  
Binary Networks ◽  
Weighted Rank

Complex network response to node loss is a central question in different fields of science ranging from physics, sociology, biology to ecology. Previous studies considered binary networks where the weight of the links is not accounted for. However, in real-world networks the weights of connections can be widely different. Here, we analyzed the response of real-world road traffic complex network of Beijing, the most prosperous city in China. We produced nodes removal attack simulations using classic binary node features and we introduced weighted ranks for node importance. We measured the network functioning during nodes removal with three different parameters: the size of the largest connected cluster (LCC), the binary network efficiency (Bin EFF) and the weighted network efficiency (Weg EFF). We find that removing nodes according to weighted rank, i.e. considering the weight of the links as a number of taxi flows along the roads, produced in general the highest damage in the system. Our results show that: (i) in order to model Beijing road complex networks response to nodes (intersections) failure, it is necessary to consider the weight of the links; (ii) to discover the best attack strategy, it is important to use nodes rank accounting links weight.

scholarly journals A Method of Bus Network Optimization Based on Complex Network and Beidou Vehicle Location

2019 ◽  
Vol 11 (4) ◽  
pp. 97 ◽  
Author(s):  
Peixin Dong ◽  
Dongyuan Li ◽  
Jianping Xing ◽  
Haohui Duan ◽  
Yong Wu
Keyword(s):  
Graph Theory ◽  
Complex Network ◽  
Network Optimization ◽  
Original Network ◽  
Network Efficiency ◽  
Bus Stop ◽  
Time Performance ◽  
Network Time ◽  
Vehicle Location ◽  
Bus Stops

Aiming at the problems of poor time performance and accuracy in bus stops network optimization, this paper proposes an algorithm based on complex network and graph theory and Beidou Vehicle Location to measure the importance of bus stops. This method narrows the scope of points and edges to be optimized and is applied to the Jinan bus stop network. In this method, the bus driving efficiency, which can objectively reflect actual road conditions, is taken as the weight of the connecting edges in the network, and the network is optimized through the network efficiency. The experimental results show that, compared with the original network, the optimized network time performance is good and the optimized network bus driving efficiency is improved.

scholarly journals Application of Complex Network Principles to Key Station Identification in Railway Network Efficiency Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Li Wang ◽  
Min An ◽  
Limin Jia ◽  
Yong Qin
Keyword(s):  
Complex Network ◽  
Policy Development ◽  
Network Models ◽  
Efficiency Analysis ◽  
Physical Structure ◽  
Influential Factors ◽  
Clustering Coefficient ◽  
Network Efficiency ◽  
Railway Network ◽  
Rail Network

Network efficiency analysis becomes important in railways in order to contribute towards improving the safety and capacity of the rail network, making rail travel more attractive for passengers, and improving industry practice and informing policy development. However, a physical railway network structure is a complicated system, and the operation, maintenance, and management of such a network is a difficult task which may be affected by many influential factors. By using efficiency analysis technology for a railway network, combining physical structure with operation functions can help railway industry to optimize the railway network while improving its efficiency and reliability. This paper presents a new methodology based on complex network principles that combines the physical railway structure with railway operation strategy for a railway network efficiency analysis. In this method, two network models of railway physical and train flow networks are developed for the identification of key stations in the railway network based on network efficiency contribution in which the terms of degree, strength, betweenness, clustering coefficient, and a comprehensive factor are taken into consideration. Once the key stations have been identified and analysed, the railway network efficiency is then studied on the basis of selective and random modes of the station failures. A case study is presented in this paper to demonstrate the application of the proposed methodology. The results show that the identified key stations in the railway network play an important role in improving the overall railway network efficiency, which can provide useful information to railway designers, engineers, operators and maintainers to operate and maintain railway network effectively and efficiently.

Selection Method of Customer Partners in Customer Collaborative Product Innovation

2014 ◽  
Vol 23 (4) ◽  
pp. 423-435 ◽  
Author(s):  
Fei Li ◽  
Yu Yang ◽  
Jianzhong Xie ◽  
Aijun Liu ◽  
Qian Chen
Keyword(s):  
Complex Network ◽  
Product Innovation ◽  
Online Community ◽  
Innovation Process ◽  
Partner Selection ◽  
Small World ◽  
Selection Method ◽  
Network Efficiency ◽  
Complex Network Theory ◽  
Scale Free

AbstractPartner selection is an important aspect of the customer collaborative product innovation process and aims to select innovative customer partners from huge numbers of customers, fast and accurately. The purpose of this article is to present a quantitative partner selection method based on the complex network theory. In this method, the complex network model of the Online Community Customer Network (OCCN) is constructed, and network centrality is used as the initial index of customer partner selection. Then, network efficiency and delta centrality are used to evaluate the effect of the index. An example is presented to reflect the feasibility and efficiency of the proposed method. Results validate the small-world and scale-free properties of the OCCN and show that betweenness centrality is the most appropriate index for partner selection in the OCCN.

scholarly journals Optimal Design of Hydrometric Station Networks Based on Complex Network Analysis

2018 ◽  
Author(s):  
Ankit Agarwal ◽  
Norbert Marwan ◽  
Maheswaran Rathinasamy ◽  
Ugur Ozturk ◽  
Bruno Merz ◽  
...  
Keyword(s):  
Network Analysis ◽  
Optimal Design ◽  
Complex Networks ◽  
Complex Network ◽  
Rain Gauge ◽  
Accurate Information ◽  
Network Efficiency ◽  
Synthetic Sample ◽  
Complex Network Analysis ◽  
Hydrometric Station

Abstract. Hydrometric networks play a vital role in providing information for decision-making in water resources management. They should be set up optimally to provide as much and as accurate information as possible, and at the same time, be cost-effective. We propose a new measure, based on complex network analysis, to support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum in the last years in different areas such as brain networks, social networks, technological networks or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node ranking measure, the weighted degree-betweenness, to evaluate the importance of nodes in a network. It is compared to previously proposed measures on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to check its applicability in the optimal design of hydrometric networks. The proposed measure is evaluated using the decline rate of network efficiency and the kriging error. The results suggest that it effectively quantifies the importance of rain stations. The new measure is very useful in identifying influential stations which need high attention and expendable stations which can be removed without much loss of information provided by the station network.

scholarly journals Robustness Analysis of Air Route Network Based on Topology Potential and Relative Entropy Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guangjian Ren
Keyword(s):  
Relative Entropy ◽  
Network Theory ◽  
Robustness Analysis ◽  
Air Transport ◽  
Practical Significance ◽  
Network Efficiency ◽  
Complex Network Theory ◽  
Route Network ◽  
Size Of Giant Component ◽  
Safety And Stability

Air route network (ARN) is the important carrier of air transport, and its robustness has important influence on the safety and stability of air transport. To analyze the robustness of ARN, in this paper, a topology potential relative entropy (TPRE) model is proposed, based on topology potential (TP) and relative entropy (RE) methods. Firstly, the TPRE model is established as the theoretical basis for the research. Secondly, an air route reduction network (ARRN) model is constructed according to real Chinese ARN. Besides, the basic topology features of ARRN are given by complex network theory. To prove the applicability, objectivity, and accuracy of the proposed method, attack strategies including random, degree, betweenness, closeness, eigenvector, and Bonacich are used to attack ARRN. Eventually, the performance of ARRN robustness is analyzed by network efficiency, size of giant component, and the proposed TPRE model. This conclusion has practical significance for optimizing ARN structure and improving airspace efficiency.

scholarly journals Optimal design of hydrometric station networks based on complex network analysis

2020 ◽  
Vol 24 (5) ◽  
pp. 2235-2251 ◽  
Author(s):  
Ankit Agarwal ◽  
Norbert Marwan ◽  
Rathinasamy Maheswaran ◽  
Ugur Ozturk ◽  
Jürgen Kurths ◽  
...  
Keyword(s):  
Network Analysis ◽  
Complex Networks ◽  
Complex Network ◽  
Water Resource Management ◽  
Cost Effective ◽  
Rain Gauge ◽  
Network Efficiency ◽  
Synthetic Sample ◽  
Complex Network Analysis ◽  
Hydrometric Station

Abstract. Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.

Research and Application of Importance Degree Evaluation Method of Complex Network Cascade Connection Node Based on Load Redistribution

2014 ◽  
Vol 998-999 ◽  
pp. 1174-1177
Author(s):  
Yun Peng Zhang
Keyword(s):  
Complex Network ◽  
Network Performance ◽  
Evaluation Method ◽  
Cascading Failure ◽  
Network Efficiency ◽  
Node Importance ◽  
Critical Nodes ◽  
Cascade Connection ◽  
The One ◽  
Definition Of

This paper presented a model with overload function for cascading failure. The main differences with respect to previous models are as follows: overload function is defined for each node, according to the value of overload function, one node has th ree states: success, overload, failure. After the load decreases, an overloaded node can be success again. The evolution of topology is replaced by the evolution of value of overload function during the process of cascading failure. It’s needless to delete the failure nodes and its edges, the load will avoid the failure nodes automat ically and the decrease of network performance will be reflected by network efficiency. An evaluation method of node importance considering cascading failure is proposed, and its algorithm is presented. A new definition of node importance is proposed. The most important node is the one who see failure results in the largest decrease of networks efficiency at the end of cascading. The evaluation method can help us to find some potential critical nodes which are sensitive to the efficiency of networks but not so important intuitively. Final example verifies its efficiency and feasibility.

Analysis of the Chinese air route network as a complex network

2012 ◽  
Vol 21 (2) ◽  
pp. 028903 ◽  
Author(s):  
Kai-Quan Cai ◽  
Jun Zhang ◽  
Wen-Bo Du ◽  
Xian-Bin Cao
Keyword(s):  
Complex Network ◽  
Route Network
Sign in / Sign up

Export Citation Format

Share Document