基于遗传算法的复杂网络节点匹配问题

为提高已知匹配节点较少情况下的网络节点匹配精度,提出一种基于遗传算法的复杂网络节点匹配方法。该方法根据网络结构以及已知的部分节点匹配信息,计算节点相似度矩阵,再由遗传算法求得网络间相似度之和最大的节点匹配方案。将其应用于EA随机网络、WS小世界网络和BA无标度网络,结果表明,三种复杂网络的匹配精度均有提高。该结果验证了文中方法的有效性。

Node matching between complex networks based on genetic algorithm

Aimed at improving the matching accuracy arising from the fewer known matched nodes,this paper proposes a feasible node matching algorithm based on genetic algorithm.The algorithm consists of calculating the similarity matrix of nodes through the structure of networks and part of known matched nodes and using a genetic algorithm to produce the node matching with the maximum node matching program for similarities between two networks.The application of the algorithm to the random networks,small-world networks and scale-free networks shows some improvement in the matching accuracy,which verifies the efficiency of the proposed algorithm.