Study On Influence Factors And Methods Of Target Control Of Complex Network

In recent years,network science is one of the most popular research points.We can explore the origin of biology and study the rule of change in the complex world.The rapid development of big data technology and artificial intelligence make the research of complex networks reach a new height.The ultimate goal of studying the dynamic nature of the network and the evolution of them is to control networks.Controlling complex network means making the state of this complex network evolve toward the target state.However,in reality,many complex networks are so complex that fully controlling such network is sometimes costly or even impossible.By thinking about network control,this article focuses on the following two issues:(1)In network control process,different network structures may affect the controllability of the network.So which kind of factors will have a greater impact on the controllability of the network?(2)In network control process,the controllable parts of the network sometimes are constrained.And control input signals will also be affected by the actual factors in many other situations,so how to effectively solve the problem of control in the situation of limited driver nodes?To solve the above problems,this work studies the factors which affect the effectiveness of target control of complex network and target control method in the situation which the driver nodes are limited according to the latest research results at home and abroad.This paper explores in the following two aspects and achieves some achievements:·The exploration of target control influence factors(1)This paper explores the effect of correlations on target control of complex networks.Four kinds of degree correlations are explored in the aspect of target control on complex network.Finally,the out-in degree correlation is the most influential factor for target control of complex network,and the same conclusions are obtained through the experiments on real data sets.·Research on driver nodes limited target control methods(2)For real networks,such as: most social networks,biological networks,etc.,fulling control the entire network is sometimes unnecessary or infeasible.Based on this background,Gao et al.proposed a theory which is called target control on complex network.However,for many networks,the input signals of the network are also limited.Based on this background,we propose a method which is called a method of limited driver nodes for target control.This method is based on the control centrality of complex networks.By adjusting the match order in the iteration process of target control on complex network,the driver nodes of a complex network are limited into a target set.However,due to the property limitations of the network(isolated nodes cannot be the nodes which are controlled),the driver nodes cannot be fully limited into the set.Therefore,we finally select the ratio of the driver nodes in the target set to be the measurement index.And the correctness of the method is verified on the real network data sets.In summary,research on the controllability of complex networks can have a huge impact on social and human development.This paper focuses on the problem of target control of complex network.We explore the factors which affect the effectiveness of target control and the problem of controlling the network under the condition that the driver nodes are limited.And we get some achievements in the end.It is foreseeable that in the background of big data,network control will have a variety of control modes and will be used in many aspects of projects.