THREE-LEVEL MODEL OF KNOWLEDGE REPRESENTATION BASED ON GRAPHS

  • E. R. Muntyan Southern Federal University
Keywords: Fuzzy graph, knowledge representation model, complex technical system, data, information, knowledge

Abstract

This article is devoted to solving an important and urgent problem of knowledge representa-tion in complex technical systems. The review of existing approaches to knowledge representation is carried out. The use of a three-level structure of knowledge representation in a given subject area is justified, its formal description is performed. A three-level model of knowledge representa-tion based on graphs is developed, in which data is formed at the first level, information is formed at the second level, and knowledge is produced at the third level. The formal description of the fuzzy graph intended for simulation of complex technical systems. The perimeter security system is considered as complex technical system. The objects of the perimeter security system include sta-tionary security objects, technical devices, designed to monitor objects, and potential violators. The graph vertices correspond to the objects of the security system, and the graph edges represent different types of relationships between objects. For modeling systems with different types of infor-mation flows, the use of a graph is justified, which allows to take into account the combination of the same type, different types and multiple edges in the form of a vector. In the author's software pack-age, a three-level model based on a fuzzy graph is developed, where data is represented by vertices, information is represented by the same type of connections, and knowledge is a set of paths in the graph leading to a certain result. As a result of the simulation, the number of technical devices re-quired for the protection of a given perimeter is calculated, and the problem of distribution of zones of influence of technical devices on objects of the security system is solved. The results of experi-mental studies have shown that the approaches proposed by the author can reduce the time of obtain-ing knowledge in graphs to 1000 vertices by 16 ms.

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Published
2020-01-23
Section
SECTION II. MODELING OF PROCESSES AND SYSTEMS