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The Effect of Higher-order Structure on the Evolution of Cooperative Behavior on Scale-free Networks
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XIE Fengjie, YAO Xin, WANG Siyi
Complex Systems and Complexity Science. 2024, 21 (1): 12-19.
DOI: 10.13306/j.1672-3813.2024.01.002
In order to study the influence of higher-order structures on the evolution of cooperative behavior on scale-free networks, a network game model based on the Prisoner's Dilemma game is constructed. A second-order higher-order structure is introduced on the scale-free network, a triangular face game containing pairwise games is defined, and the higher-order structure parameters are used to link the pairwise game payoffs with the face game payoffs, and the influence of the higher-order structure on the evolution of cooperative behavior is analyzed through simulation experiments. The results show that when individuals with high connectivity prioritize cooperation and obtain high payoffs, other individuals with high connectivity will be prompted to choose cooperation, and once a stable "all-cooperative" triangular strategy structure is formed among individuals, the payoffs of each cooperator can be significantly increased, which in turn promotes the emergence of cooperative behaviors.
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A Method of Evaluating Importance of Nodes in Temporal Networks Based on Inter-layer Neighborhood Information Entropy
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HONG Cheng, JIANG Yuan, YAN Yuwei, YU Rongbin, YANG Songqing
Complex Systems and Complexity Science. 2024, 21 (1): 20-27.
DOI: 10.13306/j.1672-3813.2024.01.003
In order to identify important nodes in temporal networks, a node importance evaluation method is proposed in based on inter-layer neighborhood information entropy. Inspired by the directed flows model of temporal networks, the method introduces the parameter ω to fuse the inter-layer neighborhood topology information of node at adjacent snapshots, uses information entropy to describe the complexity of network structure, and also takes into account the global topological information. The effectiveness and applicability of the method is proved by using the SIR propagation model, Kendall correlation coefficient, Top-k metrics, and the proposed method is compared with six evaluation methods on six real datasets. The experimental results demonstrate that the method can more effectively identify the important nodes in the temporal network. Meanwhile, the identification of the nodes of with high importance is more accurate. In addition, the parameter ω can be adjusted to improve the evaluation effect of this method according to the topology of the temporal network. Last but not least, the time complexity of this method is O(mn), which is suitable for large-scale temporal networks.
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Modeling Analysis and Management Control of Dense Pedestrian Flow in a Closed Area Under the Outbreak of Infectious Diseases: Taking University Canteen as an Example
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JI Xin, XU Jiaming, YANG Ailing, YU Zilan, TANG Tieqiao
Complex Systems and Complexity Science. 2024, 21 (1): 35-42.
DOI: 10.13306/j.1672-3813.2024.01.005
In order to reduce the transmission risk of closed systems in densely populated areas during outbreaks of infectious diseases, this study focuses on the first cafeteria of the Shahe Campus of Beihang University as the research scene, and proposes 12 evacuation strategies for school cafeterias where disease transmission occurs. By conducting cellular automaton simulations, the effectiveness of these control strategies is evaluated. The simulation results indicate that implementing measures such as disinfection of entrances and exits, and isolating patients before evacuation can reduce the overall infection risk by approximately 40%. These control measures not only address the issue of evacuating individuals suspected of having COVID-19 in places of congregation, but also have practical value in handling sudden situations in specific scenarios and guiding epidemic prevention efforts.
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The Impact of Epidemic on Shanghai Stock Exchange Industry Based on Complex Networks
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LIU Jiangang, CHEN Luxia
Complex Systems and Complexity Science. 2024, 21 (1): 43-50.
DOI: 10.13306/j.1672-3813.2024.01.006
In order to explore the impact of the Covid-19 epidemic on China's stock market, the Granger causality test is used to construct a complex network model of three stages before the outbreak, the outbreak period and the normalized control of the epidemic. The comparative analysis is made from the network topology, survivability and node importance. It is found that the impact of the epidemic has significantly changed the structural relationship of the Shanghai Stock Exchange industry sectors, and the linkage effect between industry indices has weakened; the network attack simulation experiment shows that in the face of more destructive deliberate attacks, the third stage has a more durable resistance, followed by the first, second-stage network. Before and after the epidemic, the ranking of the importance of industry stocks has changed significantly. The electronics, social services, comprehensive and commercial retail industries have gradually taken an important position in the stock market; the computer, household appliances and communication industries have become important control nodes for information transmission efficiency in the stock market network. During the attack of the epidemic, the positive impact of medical biology was obvious, and it became a buffer for risk contagion in the market.
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On the Competitive Situation of Airlines and the Influencing Factors from the Perspective of Network
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WANG Yu, LEI Di, YU Jiaojiao, WEN Guobing
Complex Systems and Complexity Science. 2024, 21 (1): 66-73.
DOI: 10.13306/j.1672-3813.2024.01.009
In order to analyze the competitive pattern and factors influencing the competitive advantage of China's major domestic passenger airlines during the epidemic period, we use the TOPSIS-Entropy method and a modified Huff model to quantify the competitive advantage strength of airlines on routes, construct a weighted bipartite network of airlines-routes empowerment based on advantage strength, and study the market segmentation of airlines' competitive advantage and its static characteristics from the perspective of network. The Tobit regression model is used to analyze the factors influencing competitive advantage. The study shows that during the epidemic period, the airlines have a low degree of multi-market exposure, and the three major airlines have obvious competitive advantages, which vary greatly in city distribution and are mainly concentrated in their base cities; HU, 3U and other airlines have less obvious advantages in market competition and are more competitive and mainly around the second-tier coastal cities. The competitive advantage of airlines is constrained by a combination of factors, and the revenue during the epidemic period is more indicative of the ability to control cost.
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Analysis and Application of Chaotic System with Polynomial Absolute Valued Function
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GAO Zhengzhong, DU Xiang
Complex Systems and Complexity Science. 2024, 21 (1): 74-84.
DOI: 10.13306/j.1672-3813.2024.01.010
In order to get more complex dynamical properties, a chaotic system with cubic polynomial taking absolute value function is designed. The theoretical model of the chaotic system is described by a set of nonlinear equations with three state variables. The basic properties and the dynamic characteristics of the system like phase diagram, time domain waveform, Lyapunov exponent, Poincaré map and bifurcation diagram are analyzed. Under certain parameter conditions, the system has periodic and chaotic properties, and there are coexistence attractors or aggregation attractors when the initial values are symmetrical. In addition, when some system parameters change, the system has constant dynamic characteristics, when the initial value of the state variable changes, the dynamic characteristics of the system also remain unchanged. The correctness of the theory is verified by circuit simulation. Based on the newly designed chaotic system, an encryption scheme is designed, and the encryption performance is analyzed, which shows the effectiveness of the encryption scheme.
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Evolutionary Game Analysis of Dynamic Cooperative Behavior of Top-management Teams in Mixed Ownership Enterprises
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SONG Mei, WANG Zhenyuan, GE Yuhui, LIU Jusheng
Complex Systems and Complexity Science. 2024, 21 (1): 85-91.
DOI: 10.13306/j.1672-3813.2024.01.011
Based on the perspective of bounded rationality, this paper first constructed a dynamic game model of dynamic cooperative behavior to explore this problem. Secondly, it discussed the impact of contract fines, government incentives, cooperation costs, and cooperation revenues on the evolution of top-management team behavior. Finally, it carried out numerical simulation and correlation analysis on its evolution process. The research shows that the final strategy of the two sides in the cooperation of the senior management team of mixed ownership enterprises will be stable in the cooperation and non-cooperation strategy, and will not be stable in the cooperation and non-cooperation strategy of one party. Among them, within a certain range, increasing the penalty of contract, increasing government incentives, reducing cooperation costs, and increasing the coefficient of cooperation revenue can promote the transformation from non-cooperation to cooperation. We hope that this study can provide some reference significance for the smooth progress of the mixed reform of state-owned enterprises and form efficient institutional arrangements.
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Price Competition, Freshness-keeping Effort and Evolution Mode of Cold Chain Logistics of Agricultural Products E-commerce
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LI Chunfa, ZU Xiaotong, TIAN Gaidi
Complex Systems and Complexity Science. 2024, 21 (1): 100-108.
DOI: 10.13306/j.1672-3813.2024.01.013
Scientific and reasonable cold chain logistics mode is the key to ensure the price and freshness competitiveness of agricultural products e-commerce. For the supply chain involving two agricultural products e-commerce, e-commerce self-run cold chain logistics and third party cold chain logistics provider, the Stackelberg game model that takes into account the competition between two agricultural products e-commerce, and the dominance of third-party cold chain logistics provider, as well as the evolutionary game model for the choice of two agricultural e-commerce cold chain logistics modes is constructed. The influence of cross price elasticity, freshness demand elasticity, and preservation input cost coefficient of self-run and third-party on the evolution path is revealed through the simulation. The results show that: if the cross price elasticity, freshness demand elasticity and the third-party preservation input cost coefficient increase respectively, self-run cold chain logistics is the stable evolutionary strategy, e-commerce tends to self-run cold chain logistics. If the self-run preservation input cost coefficient increases, the third-party cold chain logistics is the stable strategy, the e-commerce tends to cooperate with the third-party cold chain logistics provider.
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Particle Swarm Optimization Algorithm Based on Labor Division and Fuzzy Control
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LI Jin, ZHANG Jihui, GAO Xueliu, ZHANG Baohua
Complex Systems and Complexity Science. 2024, 21 (1): 109-118.
DOI: 10.13306/j.1672-3813.2024.01.014
In order to overcome the shortages of the particle swarm optimization algorithm, such as low accuracy, slow convergence and falling into local optima, a particle swarm optimization algorithm based on labor division and fuzzy control is proposed, which improves the algorithm by using the division of labor, parameter adaptive adjustment and simulated annealing with distance factors. Particles are divided into scout and rearguard ones, the former searches randomly and the latter learns from the best individual solutions as well as the best global solution to ensure the diversity of population and to accelerate the search. A sigmoid function is used to adjust the inertial weight and fuzzy logic is applied to balance exploration and exploitation capability of the algorithm. The best global particle is updated according to simulated annealing with distance factors taken into account, which improves the ability of the algorithms to jump out of the local optima. Simulation experiments on 25 standard test functions show that the improved algorithm has better performance in terms of convergence accuracy, speed and stability.
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Risk Evaluation of Unsafe Behavior of Wind Power Operation Personnel Based on FOA-BP
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CHANG Dingyi, SHI Juan, QU Lili, HE Zichun, ZHANG Yinlong, ZHENG Peng
Complex Systems and Complexity Science. 2024, 21 (1): 119-125.
DOI: 10.13306/j.1672-3813.2024.01.015
In order to evaluate the risk of unsafe behavior of wind power operation and maintenance personnel and reduce the occurrence of behavioral safety accidents. On the basis of determining the set of risk factors of unsafe behavior, the risk evaluation index system of unsafe behavior is constructed. The weight and threshold of BP neural network were adjusted by fruit fly optimization algorithm, and an unsafe behavior risk assessment model based on FOA-BP was established. Taking a wind farm as an example to collect data, test the model, realize the risk evaluation of unsafe behavior, and calculate the weight of risk evaluation index. This model has good predictive performance and can evaluate the risk of unsafe behavior. Enterprises can develop targeted prevention and control measures according to the evaluation index, index weight value and risk level.
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A Traffic Strategy for Mixed Intersections Based on Platoon and Dynamic Priority
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WU Yi, WANG Qingzhi
Complex Systems and Complexity Science. 2024, 21 (1): 126-131.
DOI: 10.13306/j.1672-3813.2024.01.016
In a mixed intersection composed of autonomous and manual vehicles, the traditional traffic strategy leads to slow traffic, long waiting time, and low efficiency. To solve the problem, in this paper, platoons of vehicles are formed based on the distance between vehicles. The platoons with autonomous and manual vehicles are controlled by different traffic strategies and priorities, which effectively prevents the traffic efficiency reduction of autonomous vehicles and ensures the fairness of traffic at intersections. Simulations show that with the increase of penetration rate, the proposed strategy is superior to the traditional strategies in terms of the average speed, the average waiting time, and the average fuel consumption.
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Effects of Seasonal Transmission and Floating Population on the Dynamics of Measles
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HAN Shifeng, ZHAI Xiafei, ZHAO Jijun
Complex Systems and Complexity Science. 2024, 21 (1): 139-144.
DOI: 10.13306/j.1672-3813.2024.01.018
This paper analyzes the influence of seasonality of infection rate and floating population on measles dynamics in Henan province, compares and analyzes the seasonal variation pattern of measles infection rate, and provides theoretical support for the future prevention and control of measles in China. In this paper, a SIR model including the seasonal ladder model of migrant population and infection rate was established, and the parameters in the model were estimated using the Markov Monte Carlo method, the infection rate of local mobile population and the migrant population outside the province was compared, and the influence of different infection rate models on transmission dynamics was analyzed. In the measles transmission dynamics in Henan, the influence of migrant population outside the province on measles transmission dynamics was greater than that of the local population, and the seasonal change pattern of infection rate in Henan was more in line with the step change, and the influence of migrant population on measles transmission dynamics in Henan was higher than that of seasonal infection rate. In the future measles prevention and control work, we should strengthen the monitoring of the migrant population and reasonably choose the time and population of immunization.
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