Identification of Technological Objects on the Basis of Intellectual Data Analysis

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.
Author Igor Korobiichuk (FM / IACR)
Igor Korobiichuk,,
- The Institute of Automatic Control and Robotics
, Yaroslav Smityuh - National University of Food Technologies Kiev Ukraine [National University of Food Technologies of Ukraine]
Yaroslav Smityuh,,
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, Vasil Kishenko - National University of Food Technologies Kiev Ukraine [National University of Food Technologies of Ukraine]
Vasil Kishenko,,
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, Ladanyuk Anatoliy - National University of Food Technologies Kiev Ukraine
Ladanyuk Anatoliy,,
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, Dmitriy Shevchuk - National Aviation University Kyiv Ukraine [National Aviation University]
Dmitriy Shevchuk,,
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, Viacheslav Ivashchuk - National University of Food Technologies Kiev Ukraine [National University of Food Technologies of Ukraine]
Viacheslav Ivashchuk,,
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, Regina Boyko - National University of Food Technologies Kiev Ukraine [National University of Food Technologies of Ukraine]
Regina Boyko,,
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, Igor Elperin - National University of Food Technologies Kiev Ukraine [National University of Food Technologies of Ukraine]
Igor Elperin,,
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Pages487-495
Publication size in sheets0.5
Book Szewczyk Roman, Krejsa Jiří, Nowicki Michał, Ostaszewska-Liżewska Anna (eds.): Mechatronics 2019: Recent Advances Towards Industry 4.0, Advances in Intelligent Systems and Computing, vol. 1044, 2020, Springer International Publishing, ISBN 978-3-030-29992-7, [978-3-030-29993-4], 515 p., DOI:10.1007/978-3-030-29993-4
Keywords in Englishneuro-fuzzy network, parameters of functions of belonging, algorithm studies
DOIDOI:10.1007/978-3-030-29993-4_60
URL https://link.springer.com/chapter/10.1007/978-3-030-29993-4_60
Languageen angielski
Score (nominal)20
Score sourcepublisherList
ScoreMinisterial score = 20.0, 13-12-2019, MonographChapterAuthor
Publication indicators Scopus Citations = 0
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