Propagation And Control Of Complex Networks Based On Multi-information Features

With the advent of the information age,people will be exposed to massive amounts of information in real life and the Internet every day,and the methods of communication have become diversified,instant,and virtualized.In many scenarios,information is not transmitted in a single,but multiple pieces of information are transmitted at the same time.In the process of dissemination,some information can cause a great impact.In the limited time of each day,we not only have to communicate with people in real life,but also browse and disseminate various messages on the virtual Internet,and the news spread on the Internet and the spread of information in real life influences.Therefore,the study of information transmission dynamics,that is,control strategies,is particularly important from the perspective of multiple information transmission characteristics.The results of the latest complex network theory have helped people solve many problems about information dissemination and infectious disease control.Researchers first abstract the problem by understanding it,and then construct mathematical models.Make simulation experiments and mathematical analysis on the model,adjust the model parameters on this basis,and formulate corresponding control strategies.Based on the classic model,this paper studies the influence of multi-information features on information and the spread of infectious diseases.The main work includes two aspects:(1)Based on the characteristics of multi-information propagation in practical problems,based on two classic network models,a multi-information overlay network different from the traditional network structure is constructed.In the process of the simultaneous transmission of multiple types of information,its competitiveness will affect the information transmission process to a certain extent.Therefore,the competitive consciousness of information is introduced in the classic SIS epidemic model.The greater the competition consciousness,the more the average degree of the network Larger,it has a greater probability of connection to surrounding nodes,forming a greater attractive capacity.Through theoretical analysis and experimental simulation,it is found that competition awareness will speed up or inhibit the spread of information to varying degrees,so that information with high competition awareness will have a larger scale of transmission.This conclusion is in line with the"Matthew Effect"in reality.In addition,competition awareness will also speed up the spread of information,so you can control the spread of bad information by controlling information that is highly competitive,which helps to understand and predict potential communication trends.(2)In the spread of epidemics,not only the physical contact of the actual physical level,but also the prevention of information dissemination at the virtual level.Defensive measures are taken by understanding the prevention information,thereby reducing the actual infection of the disease.Based on this,a two-layer infectious disease transmission model S_CS_UIR with prevention awareness is proposed,where the virtual network represents the spread of disease prevention information,the real network represents the physical spread of infectious diseases,and the interaction of the two layers of networks affects the actual disease.Communication effect.Multi-layer heterogeneous networks are formed by combining different network topologies and multiple average degree distribution networks on real and virtual networks.Numerical analysis is performed to discuss the impact of prevention awareness and other networking parameters on disease transmission.The density map shows the final scale of the disease.The analysis shows that the transmission of infectious diseases has a weakening effect under the circumstance that the information interaction of virtual network with prevention awareness is more frequent than the actual interaction.