Expansion of fuzzy sets to account for doubts and uncertainty of experts based on a modified aggregation operator

Abstract

Quantification in collective behavior and decision-making in fuzzy conditions is crucial to ensure the health and safety of the population. The task of modeling and predicting behavior in fuzzy conditions, as is known, has increased complexity due to a large number of factors from which an NP-complete multi-criteria problem is formed. There is a difficulty in quantifying the impact of fuzzy factors using a mathematical model. In this regard, the paper proposes a stochastic model of human decision- making to account for doubts and uncertainty of experts based on a modified aggregation operator. The developed fuzzy model combines fuzzy logic into a conventional model of social behavior. Unlike existing models and applications, this approach uses fuzzy sets and membership functions to describe the evacuation process in an emergency situation. The purpose of this work is to expand fuzzy sets to account for doubts and uncertainty of experts based on a modified aggregation operator and analysis of existing solutions. The problem statement in this paper is as follows: to form a set of fuzzy sets to account for doubts and uncertainty of experts based on a modified aggregation operator. The scientific novelty lies in the formation of a set of factors that form fuzzy rules for making dynamic decisions. The practical value of the work lies in the creation of fuzzy sets to account for doubts and uncertainty of experts based on a modified aggregation operator [1-3]. To implement the proposed model, the process of social behavior during evacuation, independent variables are determined. These variables include measurements related to social factors, in other words, the behavior of individual subjects and individual small groups, which are fundamental at an early stage of evacuation.