scholarly journals Analysis on Topological Properties of Dalian Hazardous Materials Road Transportation Network

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Pengyun Chong ◽  
Bin Shuai ◽  
Shaowei Deng ◽  
Jianting Yang ◽  
Hui Yin
Keyword(s):  
Network Model ◽  
Transportation Network ◽  
Network Models ◽  
Node Degree ◽  
Power Law Distribution ◽  
Road Transportation ◽  
Service Network ◽  
Scale Free ◽  
Physical Network ◽  
Network Properties

To analyze the topological properties of hazardous materials road transportation network (HMRTN), this paper proposed two different ways to construct the cyberspace of HMRTN and constructed their complex network models, respectively. One was the physical network model of HMRTN based on the primal approach and the other was the service network model of HMRTN based on neighboring nodes. The two complex network models were built by using the case of Dalian HMRTN. The physical network model contained 154 nodes and 238 edges, and the statistical analysis results showed that (1) the cumulative node degree of physical network was subjected to exponential distribution, showing the network properties of random network and that (2) the HMRTN had small characteristic path length and large network clustering coefficient, which was a typical small-world network. The service network model contained 569 nodes and 1318 edges, and the statistical analysis results showed that (1) the cumulative node degree of service network was subjected to power-law distribution, showing the network properties of scale-free network and that (2) the relationship between nodes strength and their descending order ordinal and the relationship between nodes strength and cumulative nodes strength were both subjected to power-law distribution, also showing the network properties of scale-free network.

scholarly journals Impact analysis of two kinds of failure strategies in Beijing road transportation network

2018 ◽  
Vol 29 (01) ◽  
pp. 1850005
Author(s):  
Zundong Zhang ◽  
Xiaoyang Xu ◽  
Zhaoran Zhang ◽  
Huijuan Zhou
Keyword(s):  
Network Model ◽  
Transportation Network ◽  
Dynamic Network ◽  
Network Models ◽  
Global Network ◽  
Statistical Characteristics ◽  
Road Transportation ◽  
Road Infrastructure ◽  
Urban Road ◽  
Infrastructure Network

The Beijing road transportation network (BRTN), as a large-scale technological network, exhibits very complex and complicate features during daily periods. And it has been widely highlighted that how statistical characteristics (i.e. average path length and global network efficiency) change while the network evolves. In this paper, by using different modeling concepts, three kinds of network models of BRTN namely the abstract network model, the static network model with road mileage as weights and the dynamic network model with travel time as weights — are constructed, respectively, according to the topological data and the real detected flow data. The degree distribution of the three kinds of network models are analyzed, which proves that the urban road infrastructure network and the dynamic network behavior like scale-free networks. By analyzing and comparing the important statistical characteristics of three models under random attacks and intentional attacks, it shows that the urban road infrastructure network and the dynamic network of BRTN are both robust and vulnerable.

scholarly journals Evolving Model for the Complex Traffic and Transportation Network Considering Self-Growth Situation

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Wei Zhang ◽  
Di Xu
Keyword(s):  
Power Law ◽  
Transportation Network ◽  
The Self ◽  
Node Degree ◽  
Power Law Distribution ◽  
Scale Free ◽  
Scaling Parameter ◽  
Growth Phenomenon ◽  
Airline Network ◽  
Evolving Model

It has been approved that the scale-free feature exists in various complex networks, such as the internet, the cell or the biological networks. In order to analyze the influence of the self-growth phenomenon during the growth on the structure of traffic and transportation network, we formulated an evolving model. Based on the evolving model, we prove in mathematics that, even that the self-growth situation happened, the traffic and transportation network owns the scale-free feature due to that the node degree follows a power-law distribution. A real traffic and transportation network, China domestic airline network is tested to consolidate our conclusions. We find that the airline network has a node degree distribution equivalent to the power-law of which the estimated scaling parameter is about 3.0. Moreover the standard error of the estimated scaling parameter changes according to the self-growth probability. Our findings could provide useful information for determining the optimal structure or status of the traffic and transportation network.

The study of genetic information flux network properties in genetic algorithms

2015 ◽  
Vol 26 (07) ◽  
pp. 1550076
Author(s):  
Zhengping Wu ◽  
Qiong Xu ◽  
Gaosheng Ni ◽  
Gaoming Yu
Keyword(s):  
Genetic Algorithms ◽  
Empirical Analysis ◽  
Degree Distribution ◽  
Genetic Information ◽  
Selection Pressure ◽  
Selective Pressure ◽  
Node Degree ◽  
Scaling Exponent ◽  
Scale Free ◽  
Network Properties

In this paper, an empirical analysis is done on the information flux network (IFN) statistical properties of genetic algorithms (GA) and the results suggest that the node degree distribution of IFN is scale-free when there is at least some selection pressure, and it has two branches as node degree is small. Increasing crossover, decreasing the mutation rate or decreasing the selective pressure will increase the average node degree, thus leading to the decrease of scaling exponent. These studies will be helpful in understanding the combination and distribution of excellent gene segments of the population in GA evolving, and will be useful in devising an efficient GA.

Scale-Free Networks Based on the Value of Interest

2013 ◽  
Vol 753-755 ◽  
pp. 2959-2962
Author(s):  
Jun Tao Yang ◽  
Hui Wen Deng
Keyword(s):  
Network Model ◽  
Power Law ◽  
Scale Free Network ◽  
Power Law Distribution ◽  
Scale Free ◽  
Distribution Property ◽  
Scale Free Networks ◽  
Free Model ◽  
Free Network ◽  
Interest Model

Assigning the value of interest to each node in the network, we give a scale-free network model. The value of interest is related to the fitness and the degree of the node. Experimental results show that the interest model not only has the characteristics of the BA scale-free model but also has the characteristics of fitness model, and the network has a power-law distribution property.

scholarly journals OPTIMASI JARINGAN TRANSPORTASI JALAN PERKOTAAN DENGAN PENDEKATAN METODE DYNAMIC BAIA11CED SCORECARD (Studi Kasus Pengembangan Perkotaan BSD City)

2019 ◽  
Vol 24 (1) ◽  
pp. 1
Author(s):  
Haris Muhammadun
Keyword(s):  
Dynamic Programming ◽  
Balanced Scorecard ◽  
Traffic Congestion ◽  
Performance Indicator ◽  
Transportation Network ◽  
Road Transportation ◽  
Service Network ◽  
Integration Management ◽  
Infrastructure Network ◽  
Transportation Theory

ABSTRACTTraffic congestion is a common cities problem. 111e sihwtion happened because of the imbalanced between demand -siqrply of the roads and the amount of vehicles. Many solutions have been carried out to solve the problem but only solve partially, the solution should be integratedsystem between infrastructure network and service nehvork, together in one good system. Optimation road transportation network in cities use dynamic balanced scorecard methode, is approach be plan with concept integration management strategic theory(balanced scorecard) and technic transportation theory (4 step models : trip generation, trip distribution, modal split, traffic assignment), and supporting by dynamic programming. The goal of the research is to improve the quality and quantity of the infrastructure network and effectivity-effisiency of the service network, so achive balanced traffic at the end traffic become safty, normally, and fluently. This condition, its mind fuel consumtion low. Key performance indicator (KPI), decided by technic guidence from the transportation ministry, the public work ministry, and the other referency.Key Words : infrastructure, service network, traffic congestion, traffic modelling, dynamic programming, balanced scorecard

scholarly journals A New Complex Network Model with Multiweights and Its Synchronization Control

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xin-lei An ◽  
Li Zhang
Keyword(s):  
Complex Network ◽  
Network Model ◽  
Weight Distribution ◽  
Control Strategies ◽  
Network Models ◽  
Lyapunov Stability Theory ◽  
Practical Significance ◽  
Node Degree ◽  
Edge Weight ◽  
Node Weight

Based on the weighted complex network model, this paper establishes a multiweight complex network model, which possesses several different weights on the one edge. According to the method of network split, the complex network with multiweights is split into several different complex networks with single weight. Some new static characteristics, such as node weight, node degree, node weight strength, node weight distribution, edge weight distribution, and diversity of weight distribution are defined. Then, by using Lyapunov stability theory, the adaptive feedback synchronization controller is designed, and the complete synchronization of the new complex network model is investigated. Two numerical examples of a triweight network model with the same and diverse structure are given to demonstrate the effectiveness of the control strategies. The synchronization design can achieve good results in the same and diverse structure network models with multiweights, which enrich complex network and control theory, so has certain theoretical and practical significance.

scholarly journals On the Distributions of Subgraph Centralities in Complex Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Faxu Li ◽  
Liang Wei ◽  
Haixing Zhao ◽  
Feng Hu
Keyword(s):  
Complex Networks ◽  
Probability Distributions ◽  
Network Connectivity ◽  
Network Models ◽  
Small World ◽  
Small World Networks ◽  
Power Law Distribution ◽  
Scale Free ◽  
Scale Free Networks ◽  
Complex Network Models

Subgraph centrality measure characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than large ones, which makes this measure appropriate for characterizing network motifs. This measure is better in being able to discriminate the nodes of a network than alternate measures. In this paper, the important issue of subgraph centrality distributions is investigated through theory-guided extensive numerical simulations, for three typical complex network models, namely, the ER random-graph networks, WS small-world networks, and BA scale-free networks. It is found that these three very different types of complex networks share some common features, particularly that the subgraph centrality distributions in increasing order are all insensitive to the network connectivity characteristics, and also found that the probability distributions of subgraph centrality of the ER and of the WS models both follow the gamma distribution, and the BA scale-free networks exhibit a power-law distribution with an exponential cutoff.

scholarly journals Systems biology approach highlights mechanistic differences between Crohn’s disease and ulcerative colitis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pedro A. Ruiz Castro ◽  
Hasmik Yepiskoposyan ◽  
Sylvain Gubian ◽  
Florian Calvino-Martin ◽  
Ulrike Kogel ◽  
...  
Keyword(s):  
Wound Healing ◽  
Network Model ◽  
Molecular Mechanisms ◽  
Network Models ◽  
Permeability Model ◽  
Data Repositories ◽  
Public Data ◽  
Transcriptional Changes ◽  
Network Properties ◽  
Available Information

AbstractThe molecular mechanisms of IBD have been the subject of intensive exploration. We, therefore, assembled the available information into a suite of causal biological network models, which offer comprehensive visualization of the processes underlying IBD. Scientific text was curated by using Biological Expression Language (BEL) and compiled with OpenBEL 3.0.0. Network properties were analysed by Cytoscape. Network perturbation amplitudes were computed to score the network models with transcriptomic data from public data repositories. The IBD network model suite consists of three independent models that represent signalling pathways that contribute to IBD. In the “intestinal permeability” model, programmed cell death factors were downregulated in CD and upregulated in UC. In the “inflammation” model, PPARG, IL6, and IFN-associated pathways were prominent regulatory factors in both diseases. In the “wound healing” model, factors promoting wound healing were upregulated in CD and downregulated in UC. Scoring of publicly available transcriptomic datasets onto these network models demonstrated that the IBD models capture the perturbation in each dataset accurately. The IBD network model suite can provide better mechanistic insights of the transcriptional changes in IBD and constitutes a valuable tool in personalized medicine to further understand individual drug responses in IBD.

scholarly journals Ripple-Spreading Network Model Optimization by Genetic Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Xiao-Bing Hu ◽  
Ming Wang ◽  
Mark S. Leeson
Keyword(s):  
Genetic Algorithm ◽  
Complex Network ◽  
Network Model ◽  
Real World ◽  
Network Models ◽  
Small World ◽  
Network Systems ◽  
Scale Free ◽  
Apply Genetic ◽  
Network Topologies

Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM) is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs) of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA) to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

Multilayer Network Models

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Network Models ◽  
Null Models ◽  
Emergent Properties ◽  
Multilayer Networks ◽  
Scale Free ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Network Properties ◽  
Randomization Algorithms ◽  
Network Ensembles

This chapter presents the existing modelling frameworks for multiplex and multilayer networks. Multiplex network models are divided into growing multiplex network models and null models of multiplex networks. Growing multiplex networks are here shown to explain the main dynamical rules responsible to the emergent properties of multiplex networks, including the scale-free degree distribution, interlayer degree correlations and multilayer communities. Null models of multiplex networks are described in the context of maximum-entropy multiplex network ensembles. Randomization algorithms to test the relevant of network properties against null models are here described. Moreover, Multi-slice temporal networks Models capturing main properties of real temporal network data are presented. Finally, null models of general multilayer networks and networks of networks are characterized.

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