Optimal intervention simulation method and system for panic emotion in crowd evacuation

Abstract

The invention provides an optimal intervention method for panic emotion in crowd evacuation, and the method achieves the maximization of intervention income through the adaptive adjustment of manual intervention intensity, and comprises the steps that firstly, the process of crowd emotion infection is analyzed through building an emotion infection model based on a random event; the infection trendand the recovery trend of the crowd at each moment are quantified by using the event occurrence intensity, so that targeted manual intervention can be invested; secondly, in order to accurately quantify the input manual intervention, an intervention model based on the hux process is provided, the model can adaptively adjust the intervention intensity according to the change of the crowd event occurrence intensity, and the infection rate and the recovery rate are regulated and controlled in real time to control the emotional infection; and finally, in order to consider the cost and income, theoptimal intervention intensity is input, the optimal intervention intensity is converted into a maximum yield problem, and an optimal solution is obtained by using an artificial bee colony optimization intervention emotional infection situation algorithm.

Description

technical field [0001] The present disclosure relates to the technical field of crowd emotion intervention analysis, in particular to a simulation method and system for optimizing panic intervention in crowd evacuation. Background technique [0002] The statements in this section merely mention background art related to the present disclosure and do not necessarily constitute prior art. [0003] In the face of emergencies, the crowd will have negative emotions such as anxiety and panic. These emotions will spread among the crowd and make people panic and irrational. If they are not controlled, there will be serious consequences. Research on emotional intervention has also attracted more and more attention from researchers. [0004] The inventor finds that there are following technical problems in the prior art: [0005] At present, the original emotion modeling methods include micro-emotion modeling and macro-emotion modeling; among them, the micro-emotional infection mode...

AI Technical Summary

Problems solved by technology

[0005] At present, the original emotion modeling methods include micro-emotion modeling and macro-emotion modeling; among them, the micro-emotional infection model describes the details of emotional transmission, although it can clearly describe the process of an individual from no emotion to emotion , is good at describing the details of emotional interaction between people, but the intervention measures based on the micro are limited by the model and cannot adjust the intensity of emotional intervention according to the real-time population infection situation and ensure the rational allocation of resources; the current macro dynamic models of emotions are all The deterministic model, that is, uses the mean field theory, which ignores the above-mentioned influencing factors and regards the crowd as a homogeneous individual. This theory replaces the sum of individual infection effects with the average infection effect by constructing a differential equation. Infected people Evolution and development is based on a deterministic formula, so this process cannot describe the randomness brought about by the heterogeneity of the population, and the macro-based infection model does not consider direct regulation of the infection rate and recovery rate

Images