At present, most ecological competition networks are characterized by integer-order systems, and system behavior is only affected by the current moment. In this paper, a fractional time-delay predator-prey model with independent non-cross propagation is proposed. Time delay is selected as the bifurcation parameter. The stability and bifurcation problems of the model are studied through analyzing the distribution of the roots of the corresponding characteristic equation under the influence of different orders, and the stability conditions and Hopf bifurcation criteria induced by time delay are established. Finally, the accuracy of the theoretical results is verified by numerical simulations.

The measurement method of node influence based on network structure features focuses on considering the information of neighbor nodes, ignoring the difference in topology structure between nodes. To solve this problem, this paper proposes an algorithm for measuring node influence based on network structure. First, the effective distance hidden behind the network is introduced, and the importance of nodes is measured from two perspectives. Secondly, in order to overcome the influence of subjective factors in angle fusion, the influence of nodes in the complex network is calculated by using the VIKOR method in the multi-attribute decision making theory, and is sorted. In six real networks, numerical simulation experiments are carried out by using SIR model, and the ranking differentiation and accuracy are compared with other centrality algorithms. Experimental results show that the proposed method can not only obtain more accurate sorting results, but also effectively reduce the occurrence frequency of the same sorting nodes.

The paper presents a new opinion dynamic model based on the Friedkin-Johnsen model by studying the phenomenon that the human behaviours are usually influenced by their neighbours in social networks. Firstly, taking the leader as the main body, the agent is divided into several viewpoint group systems with strong connected structures. Secondly, multi-leaders game control is used to add leader game strategies to the progress of opinion dynamic and complex co-evolution, so that each opinion group can form an optimal solution. To look for the optimal control strategy, a coupled Hamilton-Jacobi-Bellman (HJB) equation is established. Finally, several simulations are used to illustrate the formation of opinion groups in social networks to stable convergence.

Based on the Lyapunov stability theory, the theoretical analysis shows that under appropriate conditions, the drive-response network can achieve global synchronization through adaptive pinning control method. This method is more general and convenient. At the same time, this paper designs a secure communication system based on chaotic masking technology, which can realize one-to-many real-time transmission of information, and has the characteristics of fast decryption speed and high security. Finally, the correctness of the theoretical results is verified by numerical simulation.

The optimization of platform regulation strategy is the key to ensure the compliance and legality of suppliers and anchors in live broadcast e-commerce. Aiming at the interest relationship, behavior strategy and game relationship of suppliers, live broadcasting platform and anchor, this paper constructs the behavior strategy evolution game model of the three, reveals the behavior strategy evolution law of live broadcasting e-commerce under the platform regulation, and uses Netlogo to simulate the strategy evolution process. The research shows that the appropriate punishment and restraint of the platform is helpful to standardize the behavior of suppliers and anchors; Higher platform subsidies can encourage suppliers and anchors to standardize their behavior, but at the expense of their own interests, the system is difficult to stabilize; The illegal income factor is an important factor affecting the supplier's supply strategy and anchor behavior choice. Accordingly, the basic strategies and specific measures to standardize the behavior of suppliers and anchors are put forward.

In order to better formulate policies for the development of artificial intelligence, this paper analyzes the technology convergence mechanism in the field of artificial intelligence by constructing the technology convergence network model. Based on the patent data from 2010—2019 of artificial intelligence field, combined with technology and organization dimension, this paper tries to analyzes from three aspects of technical characteristics, organization technical characteristics and organization relationship characteristics. The results show that: In the field of artificial intelligence, organization cooperation is sparse, fusion technology is relatively scattered, organization and technology have obvious core-edge structure characteristics. On the level of technical characteristics, similar technologies are easier to be converged, and technologies that have already been converged will promote new convergence; On the level of organizational technical characteristics, the common technologies owned by the orgnization will negatively affect the occurrence of convergence with other technologies; On the level of organizational relationship characteristics, the effect of cooperation between organizations on technological convergence is closely related to the development stage of the field, and the "circle of buddies" inhibits technology convergence.

The Covid-19 epidemic has a significant impact on the global economy. In this paper, the minimum spanning tree method and threshold method are combined to build a correlation network for three periods before the outbreak, domestic outbreak and global spread of the epidemic. By comparing the network topology, survivability and node importance in the three stages, it is found that the epidemic has significantly enhanced the linkage effect between global stock markets. The global stock correlation network has obvious small-world characteristics, and the betweenness of nodes obey power law distribution. In the simulation experiment of network attack, deliberate attack is more destructive than random attack, and the robustness of global stock network in three periods is enhanced successively. The importance of stocks changed significantly before and after the epidemic. Chinese mainland and Hong Kong were the first to suffer a huge impact in the epidemic, but they quickly adjusted, while Europe and The United States were only affected after the global epidemic worsened. In addition, the application of cumulative sum control chart (CUSUM) to the early warning of stock prices has also achieved good results.

For the complex decision-making behaviors of the government, core enterprises, and supporting enterprises in the collaborative operation of the strategic emerging industrial cluster ecological chain, the evolutionary game and numerical simulation are used to analyze the impact of various strategic choices on the collaborative operation of the strategic emerging industrial cluster enterprise ecological chain. The results show that: core enterprises and supporting enterprises have different sensitivities to the severity of the penalty for breach of contract, and government subsidy can effectively stimulate the enthusiasm of core enterprises to participate in the collaborative operation of the cluster enterprise ecological chain. How to allocate and reasonably accept government guidance and market regulation is the key to promote the cooperative operation of enterprise ecological chain in strategic emerging industrial clusters.

The transmission of COVID-19 in relatively closed places such as ships, prisons, hospitals, is still a public concern. We take the transmission situation on the Diamond Princess Cruise ship as an example to study the transmission dynamics of COVID-19 in a relatively closed place. The Agent-Based Modeling (ABM) method is applied to simulate the transmission dynamics of COVID-19. The Latin Hypercube sampling is proposed for parameter estimation in ABM. The simulation results show that most of the infected cases on the Diamond Princess Cruise ship were transmitted between passengers. However, at the beginning of the quarantine, the number of passengers infected by crew was much more than the number of passengers infected by other passengers. Based on this results, several control measures are designed. If at the beginning of the quarantine, the lab testing was strengthened for crew members, and the infected crew were disembarked in time, the final number of infected would be greatly reduced. Furthermore, if this measure was supplemented with the conventional control measures, the final number of infected would be further reduced.

This paper studied a bi-objective vehicle routing problem with time windows, variable speed, multiple path choice, and capacity constraints (BOVRPTWVDPC) in a complex road network aiming at minimizing the total cost of distribution and maximizing the overall customer satisfaction. In modelling of customer’s satisfaction, the factors of distribution time window and customer priority were taken into account, and in the description of vehicle speed, the traffic period and road conditions were considered. A bi-objective mixed integer programming model was established, and an improved ant colony algorithm was designed to solve the problem. The simulation results show that the proposed model and the improved algorithm are effective and have certain reference value for vehicle distribution path planning under complex road conditions.

Aiming at the potential congestion caused by vehicles taking the same path, a transportation cyber-physical system framework with real-time information is proposed. Q-learning is used as a dynamic route guidance strategy, and the frequency and modes of dynamic route guidance are studied. Simulation results show that the dynamic guidance combined with real-time traffic information can effectively improve the road capacity, and multiple guidance can alleviate the potential congestion in one-shot guidance to a certain extent. The game caused by dynamic guidance varies on the frequency and modes of the guidance.

In this study, behavioral attitudes, subjective norms and perceived behavioral control are used as mediators to explore the role of consumption motivation and cognitive level in shaping consumers' purchase behavior for green agricultural products. A survey of 432 supermarket consumers in Wuhan shows that they have a high willingness to buy safe agricultural products. The consumption motivation and cognitive level of agricultural products' quality and safety level have a positive impact on consumers' purchase behavior through behavior attitudes, subjective norms and perceived behavioral control.Consumer behavior and attitude affects the subjective norms. However, the mediating effects of behavior attitude and subjective norms are independent among consumers' consumption motivation, cognitive level and purchase behavior. Consumer behavior and attitude do not transfer to specific purchase intention and behavior through subjective norms, which provides decision-making reference for government in the supervision of agricultural product quality and safety.

There are still some weaknesses of the research on tacit knowledge transfer from the perspective of contract. To explore the systematic impact of formal/informal contracts on tacit knowledge transfer, this paper extracts four transfer mechanisms, trust level, transaction cost, patent risk and contract rigidity, and builds a SD model, then uses Vensim PLE for simulation and sensitivity analysis. The results show that, there are differences in the influence path and impact effect of formal/informal contracts, under the synergistic effect of low-level formal contracts and high-level informal contracts, tacit knowledge transfer amount is the largest. Tacit knowledge transfer is more dependent on informal contracts, which provides a basis for enterprise contract governance.

To tackle the stochastic multi-depot community home health care problem, this work formulates a stochastic programming model with chance constraint to minimize the total operation time. Moreover, an improved shuffled shepherd optimization algorithm is designed by applying crossover operation instead of the basic step updating method. Therefore, the designed approach can suitably solve the community home health care problem with discrete characteristic. Extensive experiments are carried out and the results show that the proposed approach has better performance in solving the considered problem compared with two well-known meta-heuristic methods.