Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolvi...Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolving characteristics are difficult to be measured. On that account, a dynamic evolving model of complex network with fusion nodes and overlap edges（CNFNOEs） is proposed. Firstly, we define some related concepts of CNFNOEs, and analyze the conversion process of fusion relationship and hierarchy relationship. According to the property difference of various nodes and edges, fusion nodes and overlap edges are subsequently split, and then the CNFNOEs is transformed to interlacing layered complex networks（ILCN）. Secondly,the node degree saturation and attraction factors are defined. On that basis, the evolution algorithm and the local world evolution model for ILCN are put forward. Moreover, four typical situations of nodes evolution are discussed, and the degree distribution law during evolution is analyzed by means of the mean field method.Numerical simulation results show that nodes unreached degree saturation follow the exponential distribution with an error of no more than 6%; nodes reached degree saturation follow the distribution of their connection capacities with an error of no more than 3%; network weaving coefficients have a positive correlation with the highest probability of new node and initial number of connected edges. The results have verified the feasibility and effectiveness of the model, which provides a new idea and method for exploring CNFNOE＇s evolving process and law. Also, the model has good application prospects in structure and dynamics research of transportation network, communication network, social contact network,etc.展开更多
通过运用复杂网络对B2B电商网络进行建模仿真,发现B2B网络的运行规律,提出减少平台风险的措施。分析B2B电商网络的特征和演化动因,提出网络演化的动态规则、局域择优连接规则和自演化规则;基于演化规则,在BA模型的基础上,构建更契合于B2...通过运用复杂网络对B2B电商网络进行建模仿真,发现B2B网络的运行规律,提出减少平台风险的措施。分析B2B电商网络的特征和演化动因,提出网络演化的动态规则、局域择优连接规则和自演化规则;基于演化规则,在BA模型的基础上,构建更契合于B2B电商网络的局域世界核心择优连接(Local world Core Preferred connection)演化模型;采用NetLogo软件对LCP演化模型进行仿真实验。结果验证B2B电商网络具有无标度性,发现网络具有小世界性;以及网络对随机干扰具有较强的鲁棒性。展开更多
基金supported by the National Natural Science Foundation of China(615730176140149961174162)
文摘Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolving characteristics are difficult to be measured. On that account, a dynamic evolving model of complex network with fusion nodes and overlap edges（CNFNOEs） is proposed. Firstly, we define some related concepts of CNFNOEs, and analyze the conversion process of fusion relationship and hierarchy relationship. According to the property difference of various nodes and edges, fusion nodes and overlap edges are subsequently split, and then the CNFNOEs is transformed to interlacing layered complex networks（ILCN）. Secondly,the node degree saturation and attraction factors are defined. On that basis, the evolution algorithm and the local world evolution model for ILCN are put forward. Moreover, four typical situations of nodes evolution are discussed, and the degree distribution law during evolution is analyzed by means of the mean field method.Numerical simulation results show that nodes unreached degree saturation follow the exponential distribution with an error of no more than 6%; nodes reached degree saturation follow the distribution of their connection capacities with an error of no more than 3%; network weaving coefficients have a positive correlation with the highest probability of new node and initial number of connected edges. The results have verified the feasibility and effectiveness of the model, which provides a new idea and method for exploring CNFNOE＇s evolving process and law. Also, the model has good application prospects in structure and dynamics research of transportation network, communication network, social contact network,etc.
文摘通过运用复杂网络对B2B电商网络进行建模仿真,发现B2B网络的运行规律,提出减少平台风险的措施。分析B2B电商网络的特征和演化动因,提出网络演化的动态规则、局域择优连接规则和自演化规则;基于演化规则,在BA模型的基础上,构建更契合于B2B电商网络的局域世界核心择优连接(Local world Core Preferred connection)演化模型;采用NetLogo软件对LCP演化模型进行仿真实验。结果验证B2B电商网络具有无标度性,发现网络具有小世界性;以及网络对随机干扰具有较强的鲁棒性。
