拓扑结构对动态增长的复杂网络的影响

研究在网络增长和外部目标的双重作用下，拓扑结构对复杂网络的演化产生的影响。在经典的布尔网络模型上应用进化算法进行大量仿真计算，考察在2种不同的增长规则作用下，网络向预先设定的目标函数演化时表现出的演化性能。仿真结果显示，Scale-Free网络表现出明显优于随机网络的的演化能力，而且不同的度分布对网络的演化性能有重要的影响。

Impact of Topology on Dynamic Growing Complex Networks

This paper researches the impact of topology on complex networks evolution under the influence of both network growth and external target. Extensive simulations of network evolution are performed by applying an evolutionary algorithm on the classical Boolean network to investigate the performance of two types of growing rules toward pre-established target function. The results show that the growing Scale-Free networks perform much better than the growing homogenous random graph, and the degree distribution imposes significant impact on the performance of network evolution.