scholarly journals An improved node algorithm based on the evaluation of weighted network node importance

2017 ◽  
Vol 12 (1) ◽  
pp. 62-68 ◽  
Author(s):  
Lin DengWei
Keyword(s):  
Network Node ◽  
Weighted Network ◽  
Node Importance

Application and Research of Weighted Network Node Load Evaluation Method Based on Network Contribution Degree

2014 ◽  
Vol 926-930 ◽  
pp. 1874-1877
Author(s):  
Yun Peng Zhang
Keyword(s):  
Evaluation Method ◽  
Load Flow ◽  
Network Node ◽  
Weighted Network ◽  
Weighted Networks ◽  
Node Importance ◽  
Critical Nodes ◽  
The One ◽  
Load Evaluation

At present, most of research on node importance evaluation is concentrated on static un-weighted network. For weighted networks, this paper presented a new evalution method of node importance based on load flow in the node-weighted network, and it was based on the contribution of the nodes for the whole network in the view of microscopic and macroscopic. The most important node was the one which was determined by the outputing load, inputing load and crossing load between the different nodes. The improved evaluation method could help exactly to find some critical nodes which ware sensitive to the efficiency of networks. Final, example verifies its efficiency and feasibility.

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.

Compositive Evaluation for Node Importance of Wireless Network

2011 ◽  
Vol 186 ◽  
pp. 210-214
Author(s):  
Bin Chen ◽  
Guo You Chen ◽  
Zhi Xue Wang
Keyword(s):  
Wireless Network ◽  
Evaluation Method ◽  
Network Node ◽  
Method Evaluation ◽  
Crucial Issue ◽  
Evaluation Result ◽  
Evaluation Indexes ◽  
Single Index ◽  
Node Importance ◽  
Radar Chart

For design and maintenance of wireless network, node importance evaluation is a crucial issue. But if we evaluate it with single index, result may be unilateral. If we evaluate it with different indexes simultaneously, inconsistent of results may occur. To solve these problems, a compositive evaluation method based on radar chart is proposed as well as relevant evaluation indexes. With this method, evaluation indexes are showed graphically and node importance is evaluated from different viewpoints. In this way, a compositive evaluation result can be gotten according to the size of area shaped by connection of these index values in the chart. The Application of the proposed method is showed by an example case.

scholarly journals Stability Analysis of Process Route Based on Weighted Network

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Ying Xiang ◽  
Rong Mo ◽  
Zhiyong Chang ◽  
Hu Qiao ◽  
Chunlei Li
Keyword(s):  
Production Cost ◽  
Network Node ◽  
Weighted Network ◽  
Process Route ◽  
Aero Engine ◽  
Engine Blade ◽  
The Stability ◽  
Manufacturing Time ◽  
Complex Parts ◽  
Entire Network

Aiming at the production stability of complex parts, a method based on weighted network was proposed to analyze the stability of the process routes of complex parts in order to improve the production stability. The weighted network of the process routes of complex parts was constructed by using the concept of machining cell which can transform the production cost and manufacturing time to the weights of network to do the decision-making of the process routes. Based on the production stability, the brittleness risk entropy of subsystem of weighted network was constructed by analyzing the probability of the brittle events that may lead to the collapse of the weighted network in machining cells. As the indicator of analyzing the vulnerability of weighted network node, the brittleness risk entropy can predict the easily failed subsystem in the entire network. Meanwhile, the brittle event, which may lead to the machining cell failure, was retrospect for the greater stability of the process routes. Finally, the correctness and effectiveness of this method were verified by using the manufacturing process of an aero-engine blade.

Evaluation of Highway Network Node Importance via Node Benefit Function and Weighted Node Betweenness

CICTP 2015 ◽  
2015 ◽  
Author(s):  
Shu-yun Niu ◽  
Bin Li ◽  
Wu-jun Niu ◽  
Ji-sheng Zhang ◽  
Wen-feng Liu
Keyword(s):  
Network Node ◽  
Node Importance ◽  
Benefit Function ◽  
Highway Network

C-index: A weighted network node centrality measure for collaboration competence

2013 ◽  
Vol 7 (1) ◽  
pp. 223-239 ◽  
Author(s):  
Xiangbin Yan ◽  
Li Zhai ◽  
Weiguo Fan
Keyword(s):  
Network Node ◽  
Weighted Network ◽  
Centrality Measure ◽  
Node Centrality

scholarly journals Causation of Metro Operation Accidents in China: Calculation of Network Node Importance Based on DEMATEL and ISM

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Xin Wan ◽  
Yantong Zhang ◽  
Rubing Wang ◽  
Jingfeng Yuan ◽  
Mengliu Hu ◽  
...  
Keyword(s):  
Social Impact ◽  
Safety Management ◽  
Economic Loss ◽  
Network Node ◽  
Interpretive Structural Modeling ◽  
Node Importance ◽  
Accident Causation ◽  
Managerial Implications ◽  
Safety Countermeasures ◽  
Causation Analysis

Continuous metro-operation accidents lead to serious economic loss and a negative social impact. The accident causation analysis is of great significance for accident prevention and metro operation safety promotion. Network node importance (NNI) evaluation has been widely used as a tool for ranking the nodes in complex networks; however, traditional indicators such as degree centrality (DC) are insufficient for examining accident networks. This study proposed an improved method by integrating decision making trail and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) into traditional NNI evaluation, where the key nodes are determined by both the nature of the accident network topology and the contribution of the nodes to accident development. Drawing on this method, 32 accident causal factors were identified and prioritized on the ground of 248 accident cases. It was found that 14 important factors related to staff (e.g., “driver noncompliance”), environment (e.g., “extrinsic nature disturbance”), passenger (e.g., “passenger sudden illness”), and machine (e.g., “track failures”) should be given priority in safety management due to their significant tendency of causing metro accidents. Theoretical and managerial implications were discussed to provide useful insights into the understanding of the causation of metro accidents and form a basis for metro managers to develop targeted safety countermeasures related to metro operation. The proposed hybrid method is proven effective in investigating accident networks involving sequential and casual relationships and revealing factors with high possibility to increase accidents.

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