典型文献
Preferential attachment network model with aging and initial attractiveness
文献摘要:
In this paper,we generalize the growing network model with preferential attachment for new links to simultaneously include aging and initial attractiveness of nodes.The network evolves with the addition of a new node per unit time,and each new node has m new links that with probability Πi are connected to nodes i already present in the network.In our model,the preferential attachment probability Πi is proportional not only to ki+A,the sum of the old node i's degree ki and its initial attractiveness A,but also to the aging factor(τ)i-α,where(τ)i is the age of the old node i.That is,Πi ∝(ki+A)(τ)i-α.Based on the continuum approximation,we present a mean-field analysis that predicts the degree dynamics of the network structure.We show that depending on the aging parameter α two different network topologies can emerge.For α<1,the network exhibits scaling behavior with a power-law degree distribution P(k)∝ k-γ for large k where the scaling exponent γ increases with the aging parameter α and is linearly correlated with the ratio A/m.Moreover,the average degree k(ti,t)at time t for any node i that is added into the network at time ti scales as k(ti,t)∝ti-βwhere 1/β is a linear function of A/m.For α>1,such scaling behavior disappears and the degree distribution is exponential.
文献关键词:
中图分类号:
作者姓名:
Xiao-Long Peng
作者机构:
Complex Systems Research Center,Shanxi University,Taiyuan 030006,Shanxi,China;Shanxi Center for Applied Mathematics,Shanxi University,Taiyuan 030006,Shanxi,China;Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention,Shanxi University,Taiyuan 030006,Shanxi,China
文献出处:
引用格式:
[1]Xiao-Long Peng-.Preferential attachment network model with aging and initial attractiveness)[J].理论物理,2022(03):97-103
A类:
ki+A
B类:
Preferential,attachment,network,model,aging,initial,attractiveness,In,this,paper,generalize,growing,preferential,new,links,simultaneously,include,nodes,evolves,addition,unit,each,has,that,probability,are,connected,already,present,our,proportional,not,only,sum,old,degree,also,where,That,Based,continuum,approximation,mean,field,analysis,predicts,dynamics,structure,We,show,depending,parameter,different,topologies,can,emerge,For,exhibits,scaling,behavior,power,law,distribution,large,increases,linearly,correlated,ratio,Moreover,average,any,added,into,scales,function,such,disappears,exponential
AB值:
0.436853
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