This paper uses the AR (1)-GJR (1, 1)-SKT model to describe the marginal distribution of 15 stock index returns. A hybrid R-Vine Copula model is constructed to analyze the risk contagion effect of international stock markets under the four crisis events, which include the subprime mortgage crisis, the European debt crisis, the abnormal fluctuations of the Chinese stock market in 2015 and the Sino-US trade friction in 2018. The empirical results show that the international stock markets maintain symmetrical top-to-bottom dependence characteristics in the long term. The risk contagion will cause the Kendall rank correlation coefficient and tail correlation coefficient among stock markets to rise suddenly. The subprime crisis has a strong contagious effect and a long duration, and the European debt crisis is relatively mild. In 2015, the abnormal fluctuations in the Chinese stock market had a strong contagious effect on international stock markets, but the duration was short. In 2018, the Sino-US trade friction held a weaker contagious effect on the international stock markets. China's Shanghai and Shenzhen stock markets are more integrated with Hong Kong stock market in China.

Using spillovers index approach and spillover network, this paper explores the characteristics and sources of volatility spillovers effect across 11 major stock markets. The results show that the US stock market is the center of the international volatility spillover network. The three markets of UK, France and Germany have obvious mutual spillovers, but the spillovers to other markets are weak. The total volatility spillovers index is volatile, rising significantly during the period of financial turmoil. The economic fundamentals and market contagious are both important factors.

In order to analyze the policy-driven mechanism of environmental protection industry (EPI) high-quality development, the connotation of EPI high-quality development is divided into five dimensions, and the system dynamics model of EPI high-quality development is constructed. Through simulation of four policy scenarios, the effect of different policy tools is investigated. The results show that there are significant differences in objective and timeliness between the four policy tools. Tax policy has the best incentive effect on EPI output, financial policy has long-term effect, science and technology policy (STP) has the strongest driving effect on output profit margin, and environmental regulation has the most prominent effect on pollution control. At the same time, there are strong complementarities among the four policy tools.

Mission of this research is to better capture the complexity of large-scale financial systems and overcome the insufficiency of equilibrium based neoclassical finance and behavioral finance in revealing the mechanism of financial crisis and the emergence of order. This study started from the dilemma of existing theories and the motivation of introducting complexity science. Then advances of multi-agent simulation and complex network analysis are summarized and discussed as two fundimental instruments of complexity science. Research trends of complexity science in financial research, are proposed as the result of the discussions. This study provides methodology reference and analytical tools for the theoretical research and practical applications of complex financial systems in the new era.

As a form of public opinion, view and attitude, opinion widely exists in people′s life. It is important to clarify the evolution mechanism of opinion, explicit the existing research progress, and promote the rational governance of public opinion. In view of the lack of relevant introduction of binary opinion dynamics and the separation of the relationship between binary and group opinion dynamics, this paper summarized the research status of opinion dynamics at home and abroad. Firstly, it introduces the binary opinion dynamics model from the perspective of research method and interaction characteristic; Secondly, it combed the research results of group opinion dynamics from the perspective of individual characteristic, behavior characteristic, opinion characteristic, external environment and perspective dynamics. Finally, based on the existing research, it clarifies the problems, the mechanism of opinion evolution from the empirical perspective, the strengthening of opinions and the reduction of disputes, and the relationship between the evolution of views and group decision-making, that need to be solved in the future.

It is important to obtain low intervention fire prevention and control strategy in dense building areas by detecting the key building that dominate the extent of fire spread. First, established the spread directed graph model based on the multi-scenario building group fire spread simulation results. Then,the complex network method was introduced to study the appropriate sorting method of important nodes. Furthermore, a search algorithm for the reconstruction sequence of important nodes is proposed, and the number of retrofit nodes is determined with fire loss expectation as the evaluation index. Finally, the above method is applied study the issues of fire spread prevention and control in wooden village buildings. The results show that the critical buildings and their fire protection priorities can be accurately determined by the method of this paper,but their effects are different. The risk of fire spread can be significantly reduced through improving the fire protection levels of a relatively small number of buildings.

In the post-truth era, the intensified antagonism between different groups and the decline of media credibility could lead to the prominent effect of hostile media effect. To reveal the influence of hostile media effect on the public opinion formation, we explore the interaction mechanism between opinion groups and mass media and propose an opinion dynamics model that considers media hostility and opinion leaders. We finally conduct simulation experiments on the model. The simulation results and analysis show that the real opinion of media, the probability of communication between groups and media, and the proportion of extreme opinion leaders can mediate the degree of group polarization. The results reveal quantitatively that the existence of hostile media effect has an important influence on the formation of public opinion, especially on the intensification of group polarization.

In the application of artificial intelligence, the cooperation of multi robots can solve complex problems in practical engineering and become the research hotspot. In this paper, an input-constrained finite-time consistency algorithm is proposed to solve the formation control problem of nonholonomic mobile robots. By using the analysis tools such as algebraic graph theory, modern control theory and matrix theory, the formation problem of multi-robot system is transformed into the path tracking problem by introducing the virtual navigator. It is proved that the multi-robot system can realize the finite time convergence under the condition of input saturation. And the sufficient condition is obtained in finite time. Finally, the effectiveness of the proposed algorithm is verified by computer simulation.

Invulnerability analysis is one of the core contents of power grid security research. Traditional analysis methods cannot effectively analyze the process of failure generation, and have limitations in the research of invulnerability analysis. This paper studies the invulnerability analysis of power networks based on complex network theory, and conducts an empirical analysis using Chongming District of Shanghai as an example. For random attacks and selective attacks on the power network, the changes in the network efficiency and the maximum number of connected subgraphs after the attack are obtained, and the network efficiency change rate is proposed as a parameter to evaluate the invulnerability. According to the simulation results, a segmented protection scheme based on real-time centrality closeness priority attack strategy is proposed to improve the invulnerability of the power network and ensure the safety of the power grid.

In the majority of cases, networks are beneficial. However, many times it may also be harmful, such as terrorist networks and disease spreading networks. It has become an urgent challenging problem to disintegrate these harmful networks by various methods such as immunization, block, isolation, disturbance, and attack. The core task of network disintegration is to identify the “critical nodes (edges)”. This survey firstly gives the mathematical description of network disintegration. On this basis, this survey then reviews the status of network disintegration study in the fields of operations research, network science, and computer science based on mathematical programming, the centrality metrics, the heuristic algorithms, evolutionary computation, and machine learning, respectively. Lastly, this survey presents the prospects of network disintegration study from the aspects of the target network, disintegration model, and algorithm.