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Identification of Technological Objects on the Basis of Intellectual Data Analysis

Authors:

  • Igor Korobiichuk,
  • Yaroslav Smityuh,
  • Vasil Kishenko,
  • Ladanyuk Anatoliy,
  • Dmitriy Shevchuk,
  • Viacheslav Ivashchuk,
  • Regina Boyko,
  • Igor Elperin

Abstract

Considered questions of an authentications of such difficult object as installation of bragger rectification. The considered approach allows automating the process of obtaining a neuro-fuzzy model, and revealing the main dependencies between input and output variables. The approaches considered in the article can be used for development of simulation models of heat-mass exchange processes. Resulting models can be used in control systems, which are formed on the basis of optimal, robust and scenario methods.

Metrics

Record ID
WUT1dd81388431d434fb0795dfc290cd60f
Author
Yaroslav Smityuh Yaroslav Smityuh,, External affiliation of publication: National University of Food Technologies of UkraineAuthor's external affiliation: National University of Food Technologies Kiev Ukraine
Vasil Kishenko Vasil Kishenko,, External affiliation of publication: National University of Food Technologies of UkraineAuthor's external affiliation: National University of Food Technologies Kiev Ukraine
Ladanyuk Anatoliy Ladanyuk Anatoliy,, Author's external affiliation: National University of Food Technologies Kiev Ukraine
Dmitriy Shevchuk Dmitriy Shevchuk,, External affiliation of publication: National Aviation UniversityAuthor's external affiliation: National Aviation University, Kyiv
Viacheslav Ivashchuk Viacheslav Ivashchuk,, External affiliation of publication: National University of Food Technologies of UkraineAuthor's external affiliation: National University of Food Technologies Kiev Ukraine
Regina Boyko Regina Boyko,, External affiliation of publication: National University of Food Technologies of UkraineAuthor's external affiliation: National University of Food Technologies Kiev Ukraine
Igor Elperin Igor Elperin,, External affiliation of publication: National University of Food Technologies of UkraineAuthor's external affiliation: National University of Food Technologies Kiev Ukraine
Pages
487-495
Publication size in sheets
0.50
Book
Szewczyk Roman*, Roman Szewczyk,, The Institute of Metrology and Biomedical Engineering (FM/IMBE)Faculty of Mechatronics (FM)External affiliation of publication: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP Krejsa Jiří, Jiří Krejsa,, Author's external affiliation: Faculty of Mechanical Engineering Nowicki Michał Michał Nowicki,, The Institute of Metrology and Biomedical Engineering (FM/IMBE)Faculty of Mechatronics (FM) [et al.] (eds.): Mechatronics 2019: Recent Advances Towards Industry 4.0, Advances in Intelligent Systems and Computing, vol. 1044, 2020, Springer, 515 p., ISBN 978-3-030-29992-7. DOI:10.1007/978-3-030-29993-4 Opening in a new tab
Keywords in English
neuro-fuzzy network, parameters of functions of belonging, algorithm studies
DOI
DOI:10.1007/978-3-030-29993-4_60 Opening in a new tab
URL
https://link.springer.com/chapter/10.1007/978-3-030-29993-4_60 Opening in a new tab
Language
(en) English
Score (nominal)
20
Score source
publisherList
Score
Ministerial score = 20.0, 05-05-2022, ChapterFromConference
Publication indicators
Scopus Citations = 1

Cite

RDF
Uniform Resource Identifier
https://repo.pw.edu.pl/info/article/WUT1dd81388431d434fb0795dfc290cd60f/
URN
urn:pw-repo:WUT1dd81388431d434fb0795dfc290cd60f

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or PerishOpening in a new tab system.

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