TYPE-2 FUZZY SETS IN THE TASKS OF MODELLING AND ESTIMATING OF CRITICAL SYSTEMS’S STATES WITH UNCERTAIN INPUT DATA AND THE USAGE OF EXPERTS

Abstract

A method of type-2 fuzzy sets implementation for critical systems’ modeling and state assessment tasks with uncertain input data is proposed. It is shown that the basis for solving the modeling task is designing of a fuzzy logic system with interval membership functions of type-2. The paper presents the task of further developing the process of estimating the interval output of a fuzzy system with experts involvement. An approach based on fuzzy sets is proposed for solving the task of critical systems’ modeling and states assessment. Using the example of energy grid systems, where a high degree of uncertainty is present, it is shown that the main factors that influence the appearance of uncertainty in the initial data set of such systems are caused by the lack of sufficient information in the open print and the high variability of threats under the influence of the growing pace of digitalization of business processes. An analysis of expert evaluations of the interval output of fuzzy systems based on examples of modeling complex objects in various fields of application is given. The first example demonstrates the results of modeling in the field of natural sciences with uncertain initial data for assessing the prospects of an artesian well, where the final assessment is made by an expert. The second example demonstrates the implementation of the interval fuzzy model in the task of social orientation, where the problem of recruiting personnel in social groups from the point of view of professional suitability is modeled. The third task refers to modeling in the field of medical diagnosis of diseases of the endocrine system. Evaluation by experts of the results of interval fuzzy modeling in this field makes it possible to determine the state of a person's disease for endocrine pathology and prescribe timely treatment. The given examples of evaluating the interval output of a fuzzy system, taking into account the opinion of experts, confirm the possibilities for making decisions that are adequate for the subject area in the conditions of uncertain input data. Prospects for the application of the proposed models for the problems of cyber security of critical systems are given.