According to the fact that combat SoS has a dynamic structure, is dominated by men, and refers to multi domains’ interactions, we construct a multi-layered temporal network model.Based on the model some conditional network measures are redefined, and the patterns of command and control in SoS coordination are analyzed, and some measures of SoS coordination are mined, and a method of analyzing the coordination in each domain and across domains by contrast and correlation analysis is advanced.Then the demonstration of the model and method throughwargaming data validates their effectiveness.

In this paper, we study the epidemic dynamics on tripartite networks. Many vector-borne diseases spread among three populations (human beings, vectors and animals).In response to such diseases, we propose tripartite networks. Through theoretical analysis, we find the basic reproduction number of tripartite networks is not only relevant to the ratio between the second moment and the average degree, but also to the average degree, which is different with the result on bipartite networks in essence. Through numerical analysis, we also find that the diseases on the tripartite networks are easier to propagate than that on the bipartite networks; under the same contact patterns, four infection rates have the same effect on the basic reproduction number; the diseases exist or disappear on three subnetworks at the same time.

In this paper, based on the label spreading dynamics, we propose a centrality index to identify influential nodes in complex networks, where the influence of a node is measured by how many different labels who have received. Under different spreading models, we compare our index with several traditional centrality indices in different networks, our results indicate that the performance of our index is better than others. Moreover, there are two typical advantages: 1), our algorithm does not use the structure information of networks, so which can be generalized to large-scale networks; 2), our algorithm implies a conclusion-a good receiver is also a good spreader.

The stability operation of the motor drive system is seriously affected when the motors in networks fall into chaotic motion. In this paper, coupling functions are designed to achieve asymptotically synchronization based on Lyapunov stability theory and coordination control of multi-agent. Theoretical analysis and numerical simulation results demonstrate the correctness and effectiveness of the proposed control strategy. This control strategy may play an important role in the stability operation of complex motor networks in industrial automation manufacturing.

In this paper, in order to effectively discover the important links in a network, a method of identifying critical nodes in a power network is proposed, which is based on the network structure and the node dynamics. This method combines two kinds of existing node importance evaluation indicators, which are the degree centrality and the closeness centrality, at the same time, defines two evaluation indicators considering the network dynamics. The importance of a node is determined by comprehensive considering the influence of four kinds of evaluation indicators, which overcomes the one sidedness of single evaluation indicator, can get the more accurate node importance evaluation result than using single evaluation indicator. Simulation test on IEEE14 and IEEE57 node systems verifies the rationality and effectiveness of the proposed method.

In order to cope with the increasing international logistics risk, optimizing Customs Logistics Monitoring system risk management is necessary. This article use super-network theory and method to build Customs Logistics Monitoring Super-network(CLMSN) and put forward an evaluation algorithm considering static and dynamic characteristic of nodes. Numerical analyses of examples show that the method is correct and effective in identifying high risk nodes. Using the algorithm in this paper to determine the high risk nodes and giving priority to the implementation of key monitoring can control the occurrence and spread of risk, and will effectively improve the Customs Logistics risk management.

Cooperation and competition drive the dynamic evolution of the natural social and ecological system, and the interaction of these mechanisms can have different effects on multiple networks. Based on the basis of eigenvector centrality, we propose a cooperation-competition model based on the network of networks, to give a definition that the network is a kind of competition between the external relations, but the cooperation within the relationship. To reveal the competition characteristics, we classify the cooperation strategies and competitive strategies to do some research on the influence if different cooperation strategies among module network will bring the question of resource distribution to cluster network, even the entire network, and then find out the combination of the nodes with greater importance bringing.

In order to study the relationship between network structure and evolutionary game,a high clustering coefficient and adjustable power-law network model is put forward on the basis of the “triangular structure” and “internal evolution” evolution mechanism in the network. This model possesses the same characteristics as the standard scale-free networks such as the power-law degree distribution, but with the high clustering at the same time. And on the basis of the network model, according to the numbers of cooperators that is in a node with it’s immediate neighbors and neighbors’ neighbors to determine the difference of cooperators’ inputs in public goods game, in the same time use a regulatory factor to adjust the degree of heterogeneity. The simulation proves that the heterogeneous configuration model can quickly reach the Nash equilibrium, and the adjustment factors exist an optimal range can promote the boom of cooperation on the new network model.

This paper studies the noise-enhanced pulse signal transmission in coupling neural networks composed of integrate-and-fire neurons. The coupling strengthsamong neurons and the structure of the network are described by the weight matrices. The input pulse stimulus is delivered to target neurons of the network, while all neurons in the network are driven by internal noise components. It is shown that, with the increase of noise intensity, the correlation coefficient of the firing rate of the neural network output and that of the pulse stimulus can be enhanced to an extreme point, which confirms the noise-enhanced pulse signal transmission phenomenon in coupling networks. We further analyze effects of the threshold voltage, the structure of network and the noise type on the correlation coefficient of the output-input firing rates. These results provide a practical basis for the further study of stochastic resonance to the pulse signal propagation in nervous systems.

This paper builds models of one manufacturer and one retailer recycle the waste products at the same time, to analyze market operation system when different prices settings between new products and remanufactured products. Using game theory, chaotic dynamics theory and complexity dynamics theory, we perform the theory verification and reality simulation through numerical calculation.Results show that a fast speed of price adjustment of the manufacturer or the retailer will both lead the system into chaos via period-doubling bifurcations. Focusing on the harmful effects of chaotic system, adjustment parameter can be used to control the chaos efficiently. This research whose results have a strong reference value to practical problems, has a great value both of theory and application.

In the past, some large electricity providers for marketing through traditional festivals, but the effect gradually achieve Extreme. 2009, Jack Ma created “Nov.11” and named “Singles day” and carried out marketing. The results amazed us. Different from the traditional festivals, the created holiday marketing is new trend and new field to research. This paper constructs a network of nodes and showed a batch arrival Poisson supply chain network model based on the exponential growth of the Poisson network model and analyze the nodes growth dynamic with a mean-field approach. The analysis shows the power-law exponent on stabilization distribution of attitudeis 1,furthermore, the numerical results and the theoretical values are in good agreement.

Trapping process constituted a primary problem of random walks. Based on the field survey data and the theory of complex network, four types of nodes and four types of edges were defined, and then the multiple relationship networks of Spartina alterniflora genets were constructed, which showed disassortativity. In order to explore the topological and dynamic characteristics of the multiple relationship networks of S. alterniflora genets, the random walk models with multiple traps were established. The simulation result showed that the bunches and the ramets without spikes were the major regulatory nodes of ATT in the random walks. We concluded that the horizontal spatial diffusion network patterns of S. alterniflora genets revealed by the models reflected their habitat heterogeneity patterns. Furthermore, this type of models might generally provide a reference for the analysis on the heterogeneity patterns of the habitats of other clonal plants.

In social networks, the property of society has not been fully exploited. Meanwhile, learning ability for network structure optimization is weak. So a new Memetic Relationship Learning Algorithm (MRLA) has been proposed. This paper studied the fundamentals and basic procedure of MRLA, and effectively utilized the social attribute information. The new algorithm integrated the accuracy of Memetic computation and the quickness of social relational learning. The experimental results of three real-world web data sets show the validity and feasibility of the proposed algorithms.

The urban rail transit station is an important place where the passengers gather and distribute. It plays an essential role in connecting sections in a subway network. How to effectively evaluate the influence of the stations on the network is a key point to study the network structure optimization and the operation risk reduction. Based on complex network theory, this paper established a passenger flow assignment model for the urban rail transit network. Utilizing the passenger flow data from smart cards, a concentration index of passenger flow in station and three centrality indexes of network were proposed to identify the critical stations in the network. Finally, by applying this method to the Beijing subway network, we verified its validity and it can recognize the key stations successfully. Further, we systematically analyzed the current situation of the passenger flow during rush hours of Beijing subway, and put forward some suggestions for the subway network operation.

Based on spatial activity network with the characteristics oftime varying and spatial property, searching on time varying network was studied in this paper. Combined with the characteristics of spatial activity network, search time, search path length and waiting time were introduced as evaluation indexes for search strategy. And maximum activity searching strategy, improved greedy searching strategy and maximum activity minimum distance searching strategy were proposed. It was found that using improved greedy searching strategy and maximum activity minimum distance searching strategy to search on the spatial activity network would get higher efficiency than any of other strategies. They were suitable for this type of time varying network and able to optimize the searching process.