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JOURNALS // Vestnik of Astrakhan State Technical University. Series: Management, Computer Sciences and Informatics // Archive

Vestn. Astrakhan State Technical Univ. Ser. Management, Computer Sciences and Informatics, 2021 Number 1, Pages 16–27 (Mi vagtu657)

This article is cited in 1 paper

COMPUTER SOFTWARE AND COMPUTING EQUIPMENT

Classification of short technical texts using Sugeno fuzzy inference system

A. V. Borovskiia, E. E. Rakovskaiaa, A. L. Bisikalob

a Baikal State University, Irkutsk, Russian Federation
b Irkutsk State University, Irkutsk, Russian Federation

Abstract: The paper presents the results of classification of the short technical texts on the purpose of instruments using fuzzy sets theory and fuzzy logic. An important stage in designing special-purpose technical systems is the choice of equipment with specific operational characteristics. The need to categorize short technical texts, which present a brief description of equipment, annotations, fragments of databases, appears due to the fact that information about the equipment found in thematic abstract collections, technical and design documentation or in contextual advertising is often not structured and scattered. The other problems are a large number of typos, incorrect word usage and definitions in the texts. Much attention is paid to the characteristics of the objects of research and to recording their specific features – a large number of technical terms, abbreviations, symbols. The classifying technique is described, the expediency of application of fuzzy inference of Sugeno system associated with fuzziness of the natural language, the simplicity of mathematical calculations in the course of the experiment. A Sugeno model combines the description of the objects of research in the form of linguistic rules and functional dependencies. This approach greatly facilitates the interpretation of classification results.

Keywords: short technical texts, fuzzy sets, Sugeno fuzzy inference system, classification.

UDC: 004.89

Received: 09.12.2020

DOI: 10.24143/2072-9502-2021-1-16-27



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