复杂网络社团结构稳定性测试模型的仿真分析

Simulation Analysis for Stability Test Model of Complex Network Community Structure

在对复杂网络社团结构进行稳定性测试时,由于网络社团内部节点的非线性和无序性,使得网络社团结构中各层之间的连接权重需要不断快速的进行调整。传统算法中连接权重调整速度过慢,无法对网络社团结构特征的动态变化做出准确反应,导致测试效果差的问题。提出基于特征差值模型的复杂网络社团结构稳定性测试方法。建立复杂网络社团结构在时间尺度的稳定性模型,经过在时间尺度的变换后,自旋配置能够将网络中的全部社团收敛到完全相同的状态,根据社团特征之间的最大差值计算最优社团的数目,利用稳定性评价参数的变化趋势获得最稳定状态的时刻,此时的自旋配置的分布情况即为最优的复杂网络社团结构。仿真结果表明,利用改进算法能够获得最优的复杂网络社团结构,取得了令人满意的效果。

In the paper, a stability test method for complex network community structure was proposed based on feature difference model. The stability model of the complex network community structure was established in the time scale. After the conversion in the time scale, the spin configuration can converg all communities in the network to the same state. According to the maximum difference between the community characteristics, the number of the optimal community was calculated. Using the change trend of stability evaluation parameters, the moment of the most stable state can be obtained, the distribution of the spin configuration is the optimal complex network community structure at this moment. Simulation results show that using the improved algorithm can obtain the optimal complex network com- munity structure and achieve the satisfactory results.