Complex criminal cases today present systematic characteristics of multi-factor coupling and dynamic evolution, and their investigation process faces the challenge of nonlinear information integration. Criminal suspects use anti-detection methods such as changing clothes and shoes, facial obstruction, and posture camouflage, combined with complex environmental interference, which significantly reduces the practical effectiveness of single technical means such as face recognition and video structuring. In order to resolve this problem, this article focuses on the actual needs of suspect identification and tracking, breaks through the recognition bottleneck of a single modality, systematically integrates multi-information such as video structuring, face recognition, and gait recognition, and proposes a multi-information fusion video investigation system with gait recognition as the core, which realizes the dual characterization of suspect behavior patterns and identity characteristics, and provides a new technical path for improving identity recognition capabilities and the efficiency of solving complex cases.

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.

To explore the behavioral characteristics of massive crowds under the active interaction of millions of streamers and viewers in the field of live streaming, this paper summarized the temporal patterns of live streaming workload and user behavior characteristics of the live streaming platform, taking Douyu and Huya live streaming platforms as examples, a statistical analysis of 123 consecutive days, involving more than 2.4 million anchors, and more than 726 million live streaming data. The live streaming workload has obvious intra-day and intra-week effect. Different live streaming modes have significant differences in live streaming characteristics such as the average number of viewers and followers. The lifetime of streamers and the number of viewers conform to a power law distribution. With the development of the platform, there is a strong linear correlation between the number of streamers and viewers, but its volatility is gradually increasing, reflecting the increasingly strong heterogeneity and non-uniformity of the system. It is of great significance for understanding user behavior patterns in complex systems of live streaming, mining user distribution laws and changing trends, and designing business models such as personalized recommendations.

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 order to promote the development of autonomous driving technology, this paper focuses on the lane-changing decision-making behavior of autonomous vehicles. First, the lane-changing intention is quantified objectively, and then the lane-changing collision probability and the lane-changing dynamic risky coefficient are introduced. Based on the game theory, the decision-making behavior model of the lane-changing game for autonomous vehicles is established. Besides, speed gains are considered as the objective of game gains. Therefore, autonomous vehicles can change lanes in a coordinated, safe and reasonable manner. Finally, with SUMO software, the traditional LC2013 lane-changing model and the decision-making behavior model of the lane-changing game are used for simulation experiments and comparative analysis. The results show that the decision-making behavior model of the lane-changing game has higher stability, reliability, safety and lane utilization.

With requirements of continuous improvements to customers’ service, Vehicle Routing Problems with Time Windows (VRPTW) attracted more and more attention. Aiming to minimize the total cost and to maximize customers’ satisfaction, a bi-objective integer programming model is established. A Hybrid Ant Colony Optimization (HACO) is designed to solve it. An elitist-ant strategy is set up to explore the bi-objective functions respectively and to get better non-dominant solutions. The evaporation factors are redefined to balance local and global search capabilities of the algorithm and to avoid premature convergence. NSGA-Ⅱ is used to guide the bi-objective optimizing process, a variable neighborhood search algorithm is used to expand the search space, in order to obtain the better Pareto solution set. The optimal parameter combination was determined by an orthogonal experiment, and the Solomon standard instances are used to test the performance of the algorithm. The simulation results show that the HACO can effectively solve the vehicle routing problem with time windows, and the performance of HACO has a significant improvement.

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.

To improve the robustness of urban public transport system, an edge adding strategy based on transfer is formulated. Take the bus-subway composite network in Jinan as an example, the characteristic parameters and robustness of the network are studied, and an edge adding strategy based on transfer is proposed to improve the network robustness. The research shows that the composite network has the characteristics of small world and scale-free network; The network is more vulnerable than random attack under intentional attack; The network robustness is improved significantly by the high-degree edge addition strategy under betweenness attacks, which increases the proportion of attacked stations by 50.46% when the network is paralyzed; The network robustness is improved significantly by the high-betweenness edge addition strategy under random attacks and degree attacks, which increases the proportion of attacked stations by 23.35% and 39.81% respectively.

The conditions for the spontaneous emergence of cooperation under the complex human behavior model have become the focus of many disciplines. Exploring the conditions for cooperation has both important scientific significance and theoretical value for understanding the institutional arrangements in human society. The social dilemma games provide a theoretical prototype for studying cooperation issues between multiple individuals. As a dynamic analysis method that can describe individuals′ learning and strategy adjustment processes, evolutionary game theory has been one of the most effective frameworks for studying the evolution of cooperation. This review article systematically summarizes the research progress of using the evolutionary game method to study the issues of group cooperation in social dilemma games. Specifically, the following topics are included: research progress of (1) social dilemma game models, evolutionary game theory and equilibrium analysis methods, (2) social dilemma games and the evolution of cooperation under reward/punishment mechanism and reputation mechanism, (3) social dilemma games and the evolution of cooperation with separation strategy and extortion strategy, and (4) social dilemma games and the evolution of cooperation under the network reciprocity. Finally, prospects for further research issues in this area are presented.

In order to study the impact of stop-loss trading on traders′ behavior and asset prices in the market, this paper constructs a multi-agent market model with stop-loss strategy based on the method of agent-based computational finance. The model simulation results show that when the stop-loss threshold is touched in the market, it is easy to trigger continuous stop-loss trading, resulting in a behavioral cascade between traders. This kind of transaction cascading leads to an increase in the convergence of trader behavior, an imbalance between sell orders and buy orders in the market, an abnormal collapse in market prices and a liquidity black hole.