Modelling And Analysis Of Fuzzy Opinion Based On Bounded Confidence Rules

Most of the daily behaviors and decisions of human beings in the social environment are driven by viewpoints,so understanding the opinion dynamic evolution process is the key to interpreting human choices and guiding humans.In real life,human language expression is often accompanied by uncertainty and ambiguity.This kind of uncertainty comes from human's own ignorance,emotion,preference and so on.On the other hand,it comes from environmental noise,such as the interference of the mainstream media to the public in process of diffusion.Opinion dynamics is the process of the formation and evolution of opinions through group interactions.There are phenomena that people influence and be affected in the process of interaction in a group.In order to research opinioin evolution process,based on the Heglsemann-Krause(HK)model,this paper uses the fuzzy set theory to model the opinion dynamics of bounded trust,and introduces a fuzzy inference engine to calculate the nfluence weights.For the uncertainty of the environment,Gaussian random noise is used to describe the environmental uncertainty,and the impact of the two uncertainties on the evolution process of the group public opinion is analyzed.First,the fuzzy viewpoint dynamic model based on fuzzy operation is designed.By extending the classical HK model,taking into the uncertainty of human beings account.Fuzzy variables are used to describe the human opinion.At the same time,the individual's confidence level is also represented by fuzzy variables.Through the theoretical analysis and numerical simulation of the evolutionary process of this fuzzy point of view,it shows that after many iterations of the viewpoint,most people eventually take a neutral attitude.And under the same conditions of the initial point of view,whether the final view is agreed or split into several clusters depends largely on the level of trust.The simulation results are in line with real life.At the same time,the model effectively explains the interaction and evolution process in the real world with uncertain viewpoints.Then,a fuzzy opinion dynamic model based on fuzzy rules with noise is designed.First,a fuzzy opinion model with environmental noises is proposed.The HK model is a specific and non-noisy specialization of the model.In terms of the uncertainty of human beings,we express the distance between individual viewpoints as fuzzy numbers.In terms of environmental uncertainty,we model environmental noise as Gaussian random noise.particularly,this paper uses the fuzzy inference engine to determine the weight according to opinion differences between agents.It means that depending on the degree of similarity of the viewpoint,the weight of each individual's influence on others varies from 0 to 1.Compared to the model in the previous section,the model takes into the actual situation account in real life and is closer to the real society.