定量分析识别复杂网络中的重要节点对于研究复杂网络鲁棒性和脆弱性意义重大,当前基于网络结构的节点重要性评估方法成果丰富,而基于复杂网络动力学模型的节点重要性评估方法较少.针对无向加权网络,本文首先提出了构建其对应的复杂网络...定量分析识别复杂网络中的重要节点对于研究复杂网络鲁棒性和脆弱性意义重大,当前基于网络结构的节点重要性评估方法成果丰富,而基于复杂网络动力学模型的节点重要性评估方法较少.针对无向加权网络,本文首先提出了构建其对应的复杂网络动力学模型的方法,并证明了该类复杂网络动力学模型是大范围内一致渐近稳定的;然后建立了复杂网络动力学模型的偏离均值和基于偏离均值的方差两级节点重要性评估标准;最后给出了扰动测试和破坏测试两种基于复杂网络动力学模型的节点重要性评估方法.基于复杂网络动力学模型的节点重要性评估方法不仅结合了网络拓扑结构信息,同时又结合了节点自身的特性,所以评价结果更为全面.将这两种方法用于ARPA(advanced research project agency)网络、对称无向加权网络、社交网络、Dobbs-Watts-Sabel网络和Barrat-Barthelemy-Vespignani网络的重要节点评估,并与已有的复杂网络节点重要性分析方法进行比较,证明了所提出方法的有效性.展开更多
Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and simila...Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals＇ relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each ease. Finally, we present numerical simulations for each case to verify our results.展开更多
The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the t...The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.展开更多
A software network model with multiple links is constructed on the basis of a dynamical model of a general complex network with mukiple links. The principle of network division of multiple links is introduced. Followi...A software network model with multiple links is constructed on the basis of a dynamical model of a general complex network with mukiple links. The principle of network division of multiple links is introduced. Following these principles, the software network model is decomposed into three types of subnets and different relationships between classes are revealed. Then, the dynamic analysis of software networks is presented. A sufficient condition for the stability of general complex networks is obtained followed by that of software networks. Finally, the dynamics of an open-source software system is analyzed, and their simulations are provided to demonstrate the effectiveness of the presented model.展开更多
We study the attack vulnerability of network with duplication-divergence mechanism. Numerical results have shown that the duplication-divergence network with larger retention probability a is more robust against targe...We study the attack vulnerability of network with duplication-divergence mechanism. Numerical results have shown that the duplication-divergence network with larger retention probability a is more robust against target attack relatively. Furthermore, duplication-divergence network is broken down more quickly than its counterpart BA network under target attack. Such result is consistent with the fact of WWW and Internet networks under target attack. So duplication-divergence model is a more realistic one for us to investigate the characteristics of the world wide web in future. We also observe that the exponent γ of degree distribution and average degree are important parameters of networks, reflecting the performance of networks under target attack. Our results are helpful to the research on the security of network.展开更多
The emergence of mutual knowledge is a major cognitive mechanism for the robustness of complex socio-technical systems. It has been extensively studied from an ethnomethodological point of view and empirically reprodu...The emergence of mutual knowledge is a major cognitive mechanism for the robustness of complex socio-technical systems. It has been extensively studied from an ethnomethodological point of view and empirically reproduced by multi-agent simulations. Whilst such simulations have been used to design real work settings the underlying theoretical grounding for the process is vague. The aim of this paper is to investigate whether the emergence of mutual knowledge(MK) in a group of colocated individuals can be explained as a percolation phenomenon. The followed methodology consists in coupling agent-based simulation with dynamic networks analysis to study information propagation phenomena: After using an agent-based simulation the authors generated and then analyzed its traces as networks where agents met and exchanged knowledge. Deep analysis of the resulting networks clearly shows that the emergence of MK is comparable to a percolation process. The authors specifically focus on how changes at the microscopic level in the proposed agent based simulator affect percolation and robustness. These results therefore provide theoretical basis for the analysis of social organizations.展开更多
This paper investigates the finite-time generalized outer synchronization between two complex dynamical networks with different dynamical behaviors. The two networks can be undirected or directed, and they may also co...This paper investigates the finite-time generalized outer synchronization between two complex dynamical networks with different dynamical behaviors. The two networks can be undirected or directed, and they may also contain isolated nodes and clusters. By using suitable controllers, sufficient conditions for finite-time generalized outer synchronization are derived based on the finite-time stability theory. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results. The effect of control parameters on the synchronization time is also numerically demonstrated.展开更多
Building a good supply network has a competitive advantage in every part of business. However, people rarely know the principles from which supply chain with complex organizational structure and function arise and dev...Building a good supply network has a competitive advantage in every part of business. However, people rarely know the principles from which supply chain with complex organizational structure and function arise and develop. In this paper, we develop an evolving supply network model by using complex network theory. We mainly consider three kinds of firms＇ behaviors： entering of new firms, adding new relationships and rewiring of relationships among firms. By analyzing the statistical characteristics of the evolutionary dynamics of supply network, we find that the degree distribution follows a power-law distribution. Therefore, a supply network is a scale-free network where few but significant firms have lots of connections （called ＂hub＂ or core firm）, while most firms have few connections. These results are consistent with the results in empirical researches, which will be very useful for designing a robust and effective supply network.展开更多
Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the propertie...Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the properties of biological systems where the influences of excitatory nodes have been extensively investigated while those of inhibitory nodes have been studied much less. In this paper, we consider a model of oscillatory networks of excitable Boolean maps consisting of both excitatory and inhibitory nodes, focusing on the roles of inhibitory nodes. We find that inhibitory nodes in sparse networks （smM1 average connection degree） play decisive roles in weakening oscillations, and oscillation death occurs after continual weakening of oscillation for sufficiently high inhibitory node density. In the sharp contrast, increasing inhibitory nodes in dense networks may result in the increase of oscillation amplitude and sudden oscillation death at much lower inhibitory node density and the nearly highest excitation activities. Mechanism under these peculiar behaviors of dense networks is explained by the competition of the duplex effects of inhibitory nodes.展开更多
In this paper, to better understand the impact of awareness and the network structure on epidemic transmission, we divide the population into four subpopulations corresponding to different physical states and consciou...In this paper, to better understand the impact of awareness and the network structure on epidemic transmission, we divide the population into four subpopulations corresponding to different physical states and conscious states, and we first propose a modified disease- awareness model, then verify the global stability of the disease-free and endemic equilib- ria, and finally present numerical simulations to demonstrate the theoretical analysis. By examining the spreading influences of model parameters, we find that the outbreak scale can be effectively controlled through increasing the spread rate of awareness or reducing the rate of awareness loss. That is to say, all sorts of media publicity are meaningful. Meanwhile, we find that infection will be affected by consciousness through the control variable.展开更多
文摘定量分析识别复杂网络中的重要节点对于研究复杂网络鲁棒性和脆弱性意义重大,当前基于网络结构的节点重要性评估方法成果丰富,而基于复杂网络动力学模型的节点重要性评估方法较少.针对无向加权网络,本文首先提出了构建其对应的复杂网络动力学模型的方法,并证明了该类复杂网络动力学模型是大范围内一致渐近稳定的;然后建立了复杂网络动力学模型的偏离均值和基于偏离均值的方差两级节点重要性评估标准;最后给出了扰动测试和破坏测试两种基于复杂网络动力学模型的节点重要性评估方法.基于复杂网络动力学模型的节点重要性评估方法不仅结合了网络拓扑结构信息,同时又结合了节点自身的特性,所以评价结果更为全面.将这两种方法用于ARPA(advanced research project agency)网络、对称无向加权网络、社交网络、Dobbs-Watts-Sabel网络和Barrat-Barthelemy-Vespignani网络的重要节点评估,并与已有的复杂网络节点重要性分析方法进行比较,证明了所提出方法的有效性.
基金Supported by the Foundation of Anhui Education Bureau under Grant No.KJ2007A003the Natural Science Foundation of Anhui,China under Grant No.070416225+2 种基金a Grant from the Health,Welfare and Food Bureau of the Hong Kong SAR GovernmentNSFC under Grant No.10672146supported by Shanghai Leading Academic Discipline Project,Project Number:S30104
文摘Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals＇ relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each ease. Finally, we present numerical simulations for each case to verify our results.
基金supported by National Natural Science Foundation of China under Grant No. 10675060
文摘The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.
基金supported by the Major Subject of National Science and Technology of China under Grant No.2012ZX03002002
文摘A software network model with multiple links is constructed on the basis of a dynamical model of a general complex network with mukiple links. The principle of network division of multiple links is introduced. Following these principles, the software network model is decomposed into three types of subnets and different relationships between classes are revealed. Then, the dynamic analysis of software networks is presented. A sufficient condition for the stability of general complex networks is obtained followed by that of software networks. Finally, the dynamics of an open-source software system is analyzed, and their simulations are provided to demonstrate the effectiveness of the presented model.
基金The project supported by National Natural Science Foundation of China under Grant No. 10375022Acknowledgment We thank Prof. Tang Yi for helpful discussions.
文摘We study the attack vulnerability of network with duplication-divergence mechanism. Numerical results have shown that the duplication-divergence network with larger retention probability a is more robust against target attack relatively. Furthermore, duplication-divergence network is broken down more quickly than its counterpart BA network under target attack. Such result is consistent with the fact of WWW and Internet networks under target attack. So duplication-divergence model is a more realistic one for us to investigate the characteristics of the world wide web in future. We also observe that the exponent γ of degree distribution and average degree are important parameters of networks, reflecting the performance of networks under target attack. Our results are helpful to the research on the security of network.
文摘The emergence of mutual knowledge is a major cognitive mechanism for the robustness of complex socio-technical systems. It has been extensively studied from an ethnomethodological point of view and empirically reproduced by multi-agent simulations. Whilst such simulations have been used to design real work settings the underlying theoretical grounding for the process is vague. The aim of this paper is to investigate whether the emergence of mutual knowledge(MK) in a group of colocated individuals can be explained as a percolation phenomenon. The followed methodology consists in coupling agent-based simulation with dynamic networks analysis to study information propagation phenomena: After using an agent-based simulation the authors generated and then analyzed its traces as networks where agents met and exchanged knowledge. Deep analysis of the resulting networks clearly shows that the emergence of MK is comparable to a percolation process. The authors specifically focus on how changes at the microscopic level in the proposed agent based simulator affect percolation and robustness. These results therefore provide theoretical basis for the analysis of social organizations.
基金Supported by the National Natural Science Foundation of China under Grant Nos.61203304,61203055 and 10901145the Fundamental Research Funds for the Central Universities under Grant Nos.2011QNA26,2010LKSX04,and 2010LKSX01
文摘This paper investigates the finite-time generalized outer synchronization between two complex dynamical networks with different dynamical behaviors. The two networks can be undirected or directed, and they may also contain isolated nodes and clusters. By using suitable controllers, sufficient conditions for finite-time generalized outer synchronization are derived based on the finite-time stability theory. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results. The effect of control parameters on the synchronization time is also numerically demonstrated.
基金This research is supported in part by National Natural Science Foundation of China （70571034, 70301014, 70401013） and the Fund for ＂Study on the Evolution of Complex Economic System＂ at ＂Innovation Center of Economic Transition and Development of Nanjing University＂ of State Education Ministry.
文摘Building a good supply network has a competitive advantage in every part of business. However, people rarely know the principles from which supply chain with complex organizational structure and function arise and develop. In this paper, we develop an evolving supply network model by using complex network theory. We mainly consider three kinds of firms＇ behaviors： entering of new firms, adding new relationships and rewiring of relationships among firms. By analyzing the statistical characteristics of the evolutionary dynamics of supply network, we find that the degree distribution follows a power-law distribution. Therefore, a supply network is a scale-free network where few but significant firms have lots of connections （called ＂hub＂ or core firm）, while most firms have few connections. These results are consistent with the results in empirical researches, which will be very useful for designing a robust and effective supply network.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 10975015 and 11174034the Fundamental Research Funds for the Central Universities
文摘Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the properties of biological systems where the influences of excitatory nodes have been extensively investigated while those of inhibitory nodes have been studied much less. In this paper, we consider a model of oscillatory networks of excitable Boolean maps consisting of both excitatory and inhibitory nodes, focusing on the roles of inhibitory nodes. We find that inhibitory nodes in sparse networks （smM1 average connection degree） play decisive roles in weakening oscillations, and oscillation death occurs after continual weakening of oscillation for sufficiently high inhibitory node density. In the sharp contrast, increasing inhibitory nodes in dense networks may result in the increase of oscillation amplitude and sudden oscillation death at much lower inhibitory node density and the nearly highest excitation activities. Mechanism under these peculiar behaviors of dense networks is explained by the competition of the duplex effects of inhibitory nodes.
文摘In this paper, to better understand the impact of awareness and the network structure on epidemic transmission, we divide the population into four subpopulations corresponding to different physical states and conscious states, and we first propose a modified disease- awareness model, then verify the global stability of the disease-free and endemic equilib- ria, and finally present numerical simulations to demonstrate the theoretical analysis. By examining the spreading influences of model parameters, we find that the outbreak scale can be effectively controlled through increasing the spread rate of awareness or reducing the rate of awareness loss. That is to say, all sorts of media publicity are meaningful. Meanwhile, we find that infection will be affected by consciousness through the control variable.
