Limit cycle amplitude control method in rumor propagation model

Abstract

The invention discloses a limit cycle amplitude control method in a rumor propagation model. A new rumor propagation model is built on the basis of an SIR model, in consideration that the infection rate is reduced along with the increasing of the rumor propagation nodes, a piecewise function is introduced to describe the infection rate, and rumor propagation behaviors in a complex network can be more accurately described; on the basis of the new model, a control function is introduced and is added into the model, and limit cycle amplitude appearing in the rumor propagation model is controlled, the fluctuation range of number of people who propagate a rumor is controlled.

Description

technical field [0001] The invention belongs to the field of complex network propagation dynamics, and more specifically relates to a limit cycle amplitude control method in a rumor propagation model. Background technique [0002] The basic research object of propagation dynamics is the relationship between the properties of dynamic models on different networks and the static statistical properties of the corresponding networks, including known and unknown static geometric quantities. However, the research on the spread process of infectious diseases and rumors cannot obtain data through experiments in the population like some other disciplines. Relevant data and materials can only be obtained from existing reports and records, and these data are often not enough. Comprehensive and sufficient, it is difficult to accurately determine certain parameters based on these data for forecasting and control work. Therefore, it is an important research method of current communication...

AI Technical Summary

Problems solved by technology

However, the research on the spread process of infectious diseases and rumors cannot obtain data through experiments in the population like some other disciplines. Relevant data and materials can only be obtained from existing reports and records, and these data are often not enough. Comprehensive and sufficient, it is difficult to accurately determine certain parameters based on these data for forecasting and control work

Images