中文摘要：

一个新奇没有规模的网络模型基于派系(随机的尺寸的完全的潜水艇图) ，生长和优先的附件被建议。这个模型的模拟被执行。并且模型的二演变机制的必要性被验证。根据吝啬地的理论，这个模型的度分发被分析并且计算。产生网络 P (d) 的顶点的度分发功能是 2m ² m ₁⁻³(d − m ₁+ 1 )⁻³, 在 m 和 m ₁ 分别地表示新增加边的数字和派系的顶点数字的地方， d 是顶点的度，当派系 P (k) 之一是 k 是派系的度的 2m ² k ⁻³, 时。模仿并且分析结果证明两个都，顶点和派系的度分布跟随没有规模的幂定律分发。这个模型的没有规模的性质当任何一演变机制不在时消失。而且，这个模型的 randomicity 与派系的顶点数字的增长增加。

英文摘要：

A novel scale-flee network model based on clique （complete subgraph of random size） growth and preferential attachment was proposed. The simulations of this model were carried out. And the necessity of two evolving mechanisms of the model was verified. According to the mean-field theory, the degree distribution of this model was analyzed and computed. The degree distribution function of vertices of the generating network P（d） is 2m^2m1^-3（d-m1 ＋ 1）^-3, where m and m1 denote the number of the new adding edges and the vertex number of the cliques respectively, d is the degree of the vertex, while one of cliques P（k） is 2m^2Ek^-3, where k is the degree of the clique. The simulated and analytical results show that both the degree distributions of vertices and cliques follow the scale-flee power-law distribution. The scale-free property of this model disappears in the absence of any one of the evolving mechanisms. Moreover, the randomicity of this model increases with the increment of the vertex number of the cliques.