Zhang Xizhe, Wang Huaizhen, Lv Tianyang
Key Laboratory of Medical Image Computing of Northeastern University, Ministry of education, Shenyang, Liaoning, China.
School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China.
PLoS One. 2017 Apr 6;12(4):e0175375. doi: 10.1371/journal.pone.0175375. eCollection 2017.
Controlling a complex network towards a desired state is of great importance in many applications. Existing works present an approximate algorithm to find the input nodes used to control partial nodes of the network. However, the input nodes obtained by this algorithm depend on the node matching order and cannot achieve optimum results. Here we present a novel algorithm to find the input nodes for target control based on preferential matching. The algorithm elaborately arranges the matching order of the nodes to reduce the size of the input node set. The results on both synthetic and real networks indicate that the proposed algorithm outperforms the previous algorithm.
在许多应用中,将复杂网络控制到期望状态非常重要。现有工作提出了一种近似算法来找到用于控制网络部分节点的输入节点。然而,通过该算法获得的输入节点取决于节点匹配顺序,无法实现最优结果。在此,我们提出一种基于优先匹配的用于目标控制的输入节点查找新算法。该算法精心安排节点的匹配顺序以减小输入节点集的大小。在合成网络和真实网络上的结果表明,所提出的算法优于先前的算法。