Bio-Inspired Computing and Communication
Bio-Inspired Computing and Communication
复制标题
仿生计算和通信
DOI：
10.1007/978-3-540-92191-2_12
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Fallert S
中科院分区：
文献类型：
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作者：
Fallert S
研究了基于k正则图的网络模型上随机扩散过程的动态行为。将传染病传播的接触过程和易感者-被感染者-易感者模型视为原型随机传播过程。我们在一个网络上研究了这些问题，该网络分别由2倍和3倍协调随机连接的节点组成，这些节点的浓度分别为1 - p， p在0和1之间变化。改变参数pfromp= 0（无限维3正则图）top= 1（2正则图- 1D链）可以让我们研究它们在这种结构变化下的行为。这两个过程都表现出p= 0的平均场特征和p= 1的定向渗透普适性类的典型特征。通过蒙特卡罗模拟和平均场理论的应用进行了分析。采用准平稳模拟方法得到了该环境下过程的相图和临界指数。发现从平均场理论获得的临界指数的预测与模拟结果在很大范围内一致，直到p= 0.95的值，在那里系统被发现急剧跨越到一维情况。发现平均场理论给出的临界阈值估计低估了数值计算得到的所有p值的相应临界率。
The dynamic behaviour of stochastic spreading processes on a network model based on k-regular graphs is investigated. The contact process and the susceptible-infected-susceptible model for the spread of epidemics are considered as prototype stochastic spreading processes. We study these on a network consisting of a mixture of 2- and 3-fold coordinated randomly-connected nodes of concentrationpand 1 −p, respectively, with p varying between 0 and 1. Varying the parameterpfromp= 0 (3-regular graph of infinite dimension) top= 1 (2-regular graph - 1D chain) allows us to investigate their behaviour under such structural changes. Both processes are expected to exhibit mean-field features forp= 0 and features typical of the directed percolation universality class forp= 1. The analysis is undertaken by means of Monte Carlo simulations and the application of mean-field theory. The quasi-stationary simulation method is used to obtain the phase diagram for the processes in this environment along with critical exponents. Predictions for critical exponents obtained from mean-field theory are found to agree with simulation results over a large range of values forpup to a value ofp= 0.95, where the system is found to sharply cross over to the one-dimensional case. Estimates of critical thresholds given by mean-field theory are found to underestimate the corresponding critical rates obtained numerically for all values ofp.