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.

Hidden Naive Bayesian Model (HNB) and Tree Augmented Naive Bayesian Model (TAN) alleviate the strong independence assumption of Local Naive Bayesian Model (LNB) by mining the intrinsic associations between co-neighboring nodes, but ignore that there are both closely correlated nodes and relatively independent nodes in the real network. On this basis, a package criterion is designed, which divides the co-neighboring nodes into correlated co-neighboring nodes and independent co-neighboring nodes according to the degree of association. Then, packaging HNB and TAN respectively, so that the packaged-based hybrid naive Bayesian models are obtained. On FWFW networks with high average number of co-neighbors, the AUC values of the HNB and TAN models after packaging are increased by 12% and 11.6%, respectively. The experimental results show that the proposed method can effectively improve the link prediction performance and has good robustness.

The intergenerational τ has important theoretical and practical value to explore the law of virus transmission, but the probability distribution function is unknown. Therefore, this paper tries to infer the most probable form of the intergenerational interval distribution function by using the maximum entropy method, and analyzes the information of 4 986 cases of novel coronavirus from 20 countries in the world in detail, and estimates the mean and variance of the intergenerational interval of the virus on the basis of fully considering the diversity of samples. Then, based on this method, the global intergenerational interval distribution function of novel coronavirus was deduced and the basic reproduction number of China is calculated. The conclusion of this study is helpful for further objective analysis of the transmission characteristics of the virus, and provides important reference value for the formulation of regular epidemic prevention and control countermeasures and related research.

In order to better reveal the transmission mechanism of COVID-19, this paper proposes the SEAIHR dynamic model by analyzing the transmission characteristics of COVID-19, considering the self-healing of the hidden lurks and the early isolation of the lurks, introducing “h hospitalization isolation”, “recessive cure”, considering the change of prevention and control intensity, and introducing “morbidity status”. Using the real epidemic data and considering the changes of parameters in different stages, a multi model comparative test was conducted. The experimental results showed that the fitting and prediction accuracy of the SEAIHR model was significantly improved, and the fitting error was 34.4%~72.8% lower than that of the classical model in the early and middle stages of the epidemic, providing reference and guidance for epidemic prevention and control.

Noise is playing an important role in the regulation of gene transcription in biological systems. This paper studies the dynamics of gene transcription regulation system under the effects of multiplicative Gaussian white noise and additive Lévy noise. Firstly, the Lévy noise is simulated with the Janicki-Weron algorithm, and then the fourth-order Runge-Kutta algorithm is used to calculate the steady-state probability density(SPD) function of the protein concentration, then the steady state analysis of the gene transcriptional regulation system is carried out by the SPD figures. The study found that Gaussian noise intensity, Lévy noise intensity, stability index, and skewness parameter all can induce phase transitions in the gene transcription regulation system; At the same time, the increase of these parameters will cause the gene transcription regulation system to gradually the " on" state changes to the "off" state.

The image encryption algorithm based on low dimensional chaotic system has the problems of the key space small and the security not high. In this paper, an improved four-dimensional Lorenz dissipative hyperchaotic system is constructed by introducing a cubic smooth memristor model. The dynamic characteristics of the improved system such as phase portraits, dissipation, equilibrium stability, Lyapunov exponent, and bifurcation are investigated, it is proved that the system has good dynamic characteristics and chaotic attractor. Therefore, a chaotic sequence encryption algorithm based on Hash algorithm is proposed. By histogram, key space analysis,robust analysis and other verifications show that the image encryption algorithm has higher key space and can resist brute-force attack.

In order to effectively alleviate the problem of parking chaos and difficult parking during massive parking, this paper builds a convex optimization model that takes into account the interests of multiple parties, focusing on parking costs, queuing time and balancing the parking demand among multiple parking lots. First, a stable bilateral matching that minimizes parking fees is derived by using a matching game; then, the research is extended considering the interests of multiple parties at the same time, and the mathematical model constructed is a convex optimization problem, which is solved by the alternating direction multiplier method (ADMM) distributed solution. Finally, the simulation results show that the distributed optimization model based on ADMM can meet the interests of multiple parties compared with the matching game algorithm and the greedy algorithm. It is verified that the ADMM distributed optimization model is more efficient than the centralized optimization model from the aspects of privacy protection, computing time and data transfer volume. It is suitable for massive shared parking matching, and the necessity of considering the interests of multiple parties and the influence of weight coefficients on the calculation results are analyzed and verified.

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.

To discuss the Nash equilibrium strategy of the quantum prisoner's dilemma model under the influence of collective-dephasing noise channel, will collective-dephasing noise is introduced into the quantum game back, by MW quantization scheme to quantization of the prisoner's dilemma game, and a prisoner’s dilemma game under the effect of collective-dephasing noise is constructed. It is found that under the condition of the maximally entangle, each player’s payoff function shows periodicity about the parameter of the noise. And in the same period, along with the increase of the noise parameter, there is the unique pure quantum Nash equilibrium, two different pure quantum Nash equilibriums, and no pure quantum Nash equilibrium in different intervals. In the two noise intervals without a pure quantum Nash equilibrium, players were caught in a rock-paper-scissors loop. It shows that under the influence of collective-dephasing noise channel, players can reach Nash equilibrium when the noise parameters are in a specific interval.

The research aims to find the key causes and their relationships of express safety accidents. Based on the complex network theory, the Express Safety Accident Causation Network (ESACN) was constructed by setting factors as nodes and their relationships as arcs. There are 40 factors nodes extracting from personnel, express, equipment, environment, management and results. This study found that the ESACN is a small world network. Meanwhile the intermediary centrality is obvious and there is a 3-core high-density cloud in ESACN. The result indicates that casualties, express fire, express damage, property loss and transportation vehicle problems are the key factors in ESACN. Among these factors, the accumulation and damage of express have the most significant effect on accident risk transmission. The high-density correlation among the 15 factors plays a core role in the occurrence of accidents.

China's waste electrical and electronic products (WEEE) are increasing year by year. However, the formal WEEE recycling system has not been fully established, facing the problems of resource waste and environmental pollution. Based on this, considering the impact of complex traffic on WEEE transportation, a WEEE recovery network model considering real complex traffic and energy conservation and emission reduction is constructed, and compared with the WEEE recovery network model under ideal traffic. An intelligent optimization algorithm is designed to optimize the solution process of the integrated layout of WEEE recycling network, so as to minimize the construction cost of WEEE recycling network on the premise of ensuring the efficient completion of WEEE recycling. Finally, the effectiveness of the model and algorithm is verified by system simulation.

Based on the enhancement of nitrogen circulation efficiency in the watersheds, this paper explores ecological compensation strategy choices of decision-makers, constructs an evolutionary game model of boundedly rational local governments and farmers, and simulates the evolutionary equilibrium strategies. A dynamic ecological compensation policy is proposed, where compensation intensity changes with farmers' behavior, which is conducive to the government's long-term optimization of its policies. The study shows that there exists an equilibrium stability strategy for the system under static ecological compensation policy, meanwhile, the initial cooperation ratio of both parties directly affects the evolutionary rate of the system; the evolutionary trajectory under dynamic policy spirals towards a mixed strategy focus, and the cooperation ratio can be elevated by controlling the ecological compensation ceiling and other crucial factors.

In order to study the impact of traffic accidents on expressway traffic flow, a forced lane change rule was introduced based on the two-lane safe distance cellular automaton model, and a highway vehicle congestion model considering the heterogeneity of vehicles was established.The heterogeneous traffic flow on expressways was used by MATLAB numerical simulation, the impact of the duration of traffic accidents and the proportion of heavy trucks under different traffic densities on expressway congestion traffic flow was analyzed. Research shows that the duration of traffic accidents and the proportion of heavy trucks have a significant impact on the traffic flow of highway congestion; when the vehicle density is greater than 4veh/km and less than 80veh/km, the duration of the traffic accident has a significant impact on traffic flow. And the longer the duration, the greater the impact influences on the traffic flow; when the vehicle density is less than 30veh/km, the proportion of heavy trucks has a significant impact on the traffic flow, and the larger the proportion, the greater the impact influences on the traffic flow.

Aiming at the initial instability of the existing traffic cellular automata model and the initial fluctuation of data output for a long time, a new traffic flow initialization method is designed based on the principle of Fisher-Yates algorithm. This method can ensure the randomness of the location and update timing of the vehicle from entering the cell space to the subsequent evolution and update. Through the evolution experiment of the model using the new traffic flow initialization method, the results show that the initial fluctuation range is within 50 steps under the condition of arbitrary space occupancy; When the evolution update reaches 3600 steps, the output data of the model after excluding the output of the initial fluctuation interval has converged enough, and the operation of the model is stable enough.