A new differential evolution algorithm based on complex network is presented. Individuals are represented by nodes and dynamic propagation direction is represented by directed edges, thereby constructing a complex network. in particular,in the mutation stage, the mechanism of selecting the target vector based on probability using the individual objective function value and network parameter information is proposed, and the convergence factor is introduced to change the convergence speed of different function types. In the selection phase, a new sorting-based selection strategy is proposed. Finally, the proposed algorithm is tested with 21 standard test functions, and compared with some mainstream differential evolution algorithms. The test results show that the proposed algorithm has significant advantages both in convergence speed and in solution accuracy.

The seismic data taken in the geographical region under consideration are mapped to a complex network-Earthquake Network. From the perspective of complex network, we describe the spatial-temporal complexity of seismicity. In this article, we construct earthquake network and investigate it. Firstly, the results show that these earthquake networks are scale-free and small-work networks with the power-law connectivity distributions. Secondly, the scale represents co-seismic effect. Moreover, nodes and edges increase greatly after the main shock. Finally, the method of k-core decomposition is applied to the earthquake network, and an important phenomenon is found that the value of the highest layer shows obvious high-value abnormalities before some earthquakes and it will return to a stable state after the earthquake. These results reveal complex intrinsic interactions between seismic events. The earthquake network, which presented certain statistical laws, will provide a new way for us to analyze and research the seismological system.

In order to explore the strategy choice of government regulators, airports and airlines in the control of airport foreign risks, starting with the conceptual model of the government regulators, airports and airlines, a multi-party evolutionary game model of airport Foreign Object Debris risks supervision strategies is built based on game theory, which is used to analyze the stable strategy and evolution path; the system dynamics model is applied to simulate and analyze the evolutionary game process under pure strategy, static mixed strategy and dynamic government regulation strategy. The simulation results show that when the pure strategy is adopted, evolutionary game model exists effective solution, but there is no stable equilibrium solution; under the condition of mixed strategy and dynamic regulation strategy, there are stable equilibrium solutions, namely reaching the state of government supervision, airport investment, airline cooperation. Strengthening government supervision can effectively promote the airports and airlines to strengthen the control of Foreign Object Debris risks.

The fractal property is considered as the third fundamental topology features of complex networks. Studies on the fractal property of complex networks are of great significance for understanding the structure complexity of the network. The information dimension method is a useful tool to measure the fractal property of complex networks. The existing information dimension method is mainly used to analyze the fractal property of unweighted networks, and it is not fully applicable to analyze the fractal property of weighted networks. In this paper, motivated by the idea of box-covering algorithm for weighted complex networks, a fractal analysis method of weighted networks based on information dimension is proposed. We first apply this method to study the fractal property of a family of constructed “Sierpinski” weighted fractal networks, the results show that the fractal dimension of these networks obtained by the proposed method are very close to its theoretical similarity dimension. Then, we apply the proposed method to study the fractal property of three real-world weighted networks and make a detail comparison with the box-covering algorithm, results demonstrate that the proposed method is effective for the fractal scaling analysis of real-world weighted complex networks.

In this paper, the internet users on social network based on the dynamics model theory, are divided into four major categories: Unreceived users, Received users, Rumor Believe users and Rumor Deny users. We research the propagation regulations of network rumors based on the mean field theory, and then propose a new model, which applies to rumor spreading of online social network. According to the analysis of the dynamics of the model and numerical simulation experiments, the research results obtain the regulations of network rumor propagation, indicate what kind of measures should be taken in corresponding states, and demonstrate how to quiet down quickly the spread of rumor by controlling some specific factors.

In order to study the influence of the coupling strength distribution strategy for synchronization and stability of power grids,to explore a coupling mode to improve the synchronizability and stability of power grids, this paper proposes three coupling strength distribution strategies of power transmission lines, which are named EQ, TP and LB. Respertively, the EQ strategy means that all the line coupling strengths are equal. The TP strategy means that the coupling strength of a line is proportional to its power distribution which value is the case that synchronization is achieved with the equal coupling. The LB strategy means that a line coupling strength is proportion to its link betweenness. Simulation experiment is carried out on IEEE14, IEEE30, IEEE39, IEEE57 standard test net, as well as BA scale-free network and NW small-world network.The advantages and disadvantages of these three strategies are compared through synchronizability and stability of power grids. Study shows that the TP strategy is the best one, the LB strategy is the worst one among the three, the performance of the EQ strategy is in the middle.

To explore social representations of interethnic conflict and its core elements, this article used a word-association test with interethnic conflict as stimulus to collect 220 college students’ free association responses. Then complex network analysis techniques including network visualization, k-core decomposition were used for analyzing the structures of the evoked words networks, and comparing the representational differences between Yi and Han ethnic groups. Results indicated that the social representations of interethnic conflict was a 5-core multilayer network organized by the two core nuclei: war and fight, and its global meaning generated from the following 14 shared core elements and their connections: Contradiction, war, struggle, conflict, peace, ethnicity, solidarity, racial discrimination, harmony, fight, discrimination, culture, bleeding, and profit. Apart from the similar structure properties in the two groups, Yi mainly represented the interethnic conflict as a nested hierarchical network model constructed on the core axis of the death (dispute) → fight (civil strife) → war (contradiction), emphasizing a causal associations among these levels, and focused on the ethnicity element. Whilst based on the category axis of the language (strife) → interest (tussle) → war (harmony), Han socially represented the interethnic conflict from the angle of teleology, stressing on the bleeding element. The conclusion suggested that the social representation of interethnic conflict is a multi-level network structure, existing discrepancy in ethno-culture context.

User reputation is of great significance for healthy development of Internet finance and E-commerce, and it is an important research hotspot in online user's behavior analysis. Many reputation measurement methods have proposed by scholars for online rating systems. However, different reputation measurement methods are designed form different perspectives. In order to have a general understanding of user's reputation, Skyline query is introduced to identify high-reputation users in this paper.By classifying the current methods for measuring user's reputation based on clustering methods, we select a representative algorithm in each class and the user's reputation by the selected algorithms are calculated with Skyline Query. The users in the found Skyline set (not being dominated by other users) are the high-reputation users. We also analyze the rules of high-reputation users within different time periods.This paper carries out applied research on reputation from a qualitative point of view by combining multiple reputation measurement methods, broadening the breadth of the research on user reputation.

In this paper, through the establishment of model and numerical calculation based on mutual information, it is found that under the certain intensityof both additive noise and multiplicative noise, themultilevel threshold system appears suprathreshold stochastic resonance phenomenon. Increasing the value of threshold orthe number of units is more likely to make the system appear suprathreshold stochastic resonance phenomenon.But the increase of the value of threshold will weaken the effect of information transmission in the system. When the noise intensity is weak, increasing the number of output elements of each unit can improve the transmission of information in the system. However, if the number of output elements of each threshold unit is too high, the suprathreshold stochastic resonance phenomenon in the system will disappear, and the value of mutual informationalso will tends to be saturated.

In order to improve the search efficiency of particle swarm optimization and overcome the weakness of the decomposition method to deal with complex multi-objective problems, an improved self-adaptive multi-objective particle swarm optimization based on decomposition is proposed by considering the important influence of parent solutions selection and population updating on the convergence of algorithm and the distribution uniformity of solutions. To improve the convergence speed,a new fitness evaluation method is first designed to estimate solutions’ quality and the quality offspring solution won in the competition is added to the parent candidate solutions under the premise of ensuring diversity of evolutionary population by decomposition method. Next, to avoid the algorithm falling into local optimum, the personal optimal and global optimal positions are randomly selected from current particles’ neighbors or outside of neighbors when updating the particles. Last, to enhance the ability of algorithm to deal with complex problems, external archive is introduced as a candidate output population and crowding distance is used to maintain its diversity.The numerical experiments are carried out on twelve test functions and compared with five multi-objective optimization algorithms that can show the superiority of proposed algorithm.

In order to study the dynamic behavior of integer order system, scholars both in china and abroad have made great efforts and reached many important conclusions. However, in real life, the more existence is the fractional-order system. Therefore, The study of dynamic behavior of fractional-order Chua’s circuit system becomes very forward and meaningful. The main research object of this paper is the three dimensional fractional-order chua's circuit system, through the Routh-Hurwitz criterion, Lyapunov stability judgment method and matrix theory derived the sufficient condition of the asymptotic stability of the Chua’s circuit system and the selection of adaptive controller condition. Finally, the validity and rationality of the theory are verified by numerical simulation.