SPR-based Markov chain method for degree distributions of evolving networks
SPR-based Markov chain method for degree distributions of evolving networks
复制标题
基于SPR的马尔可夫链方法求解演化网络的度分布
DOI:
10.1016/j.physa.2012.01.040
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发表时间:
2012-06
期刊:
影响因子:
--
通讯作者:
Rayman-Bacchus, Lez
中科院分区:
文献类型:
--
作者:
Zhang, Xiaojun;He, Zishu;He, Zheng;Rayman-Bacchus, Lez
In this paper, we develop a stochastic process rules (SPR) based Markov chain method to calculate the degree distributions of evolving networks. This new approach overcomes two shortcomings of Shi, Chen and Liu’s use of the Markov chain method (Shi et al. 2005 [21]). In addition we show how an SPR-based Markov chain method can be effectively used to calculate degree distributions of random birth-and-death networks, which we believe to be novel. First SPR are introduced to replace traditional evolving rules (TR), making it possible to compute degree distributions in one sample space. Then the SPR-based Markov chain method is introduced and tested by using it to calculate two kinds of evolving network. Finally and most importantly, the SPR-based method is applied to the problem of calculating the degree distributions of random birth-and-death networks.
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DOI:
10.1103/physreve.82.031105
发表时间:
2010-09
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
--
作者:
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通讯作者:
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DOI:
10.1103/physreve.80.026103
发表时间:
2009-08
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
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作者:
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通讯作者:
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DOI:
10.1016/j.physa.2007.05.042
发表时间:
2007-10
影响因子:
3.3
作者:
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通讯作者:
Wenchen He;Lei Feng;Lingyun Li;Changqing Xu
DOI:
10.1103/physreve.80.011143
发表时间:
2009-06
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
--
作者:
S. M. Duarte Queirós;N. Crokidakis;Diogo O. Soares-Pinto
通讯作者:
S. M. Duarte Queirós;N. Crokidakis;Diogo O. Soares-Pinto