Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Інформаційні технології, системний анаілз та керування"'
Publikováno v:
Наукові вісті КПІ; № 1 (2017): ; 37-47
Научные вести КПИ; № 1 (2017): ; 37-47
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 37-47
"Research Bulletin of the National Technical University of Ukraine ""Kyiv Politechnic Institute"""
"""Research Bulletin of the National Technical University of Ukraine """"Kyiv Politechnic Institute"""""""
Наукові вісті НТУУ «КПІ» : міжнародний науково-технічний журнал, 2017, № 1(111)
Научные вести КПИ; № 1 (2017): ; 37-47
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 37-47
"Research Bulletin of the National Technical University of Ukraine ""Kyiv Politechnic Institute"""
"""Research Bulletin of the National Technical University of Ukraine """"Kyiv Politechnic Institute"""""""
Наукові вісті НТУУ «КПІ» : міжнародний науково-технічний журнал, 2017, № 1(111)
Background. Development of the methods for identification and assessment of early signs of heart disorders makes it possible to catch the sight of disease at its initial stage. The article considers the methods of early diagnosis of the cardiovascula
Publikováno v:
Наукові вісті КПІ; № 1 (2017): ; 24-36
Научные вести КПИ; № 1 (2017): ; 24-36
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 24-36
Научные вести КПИ; № 1 (2017): ; 24-36
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 24-36
Blackground. The issue of providing the increase of production of main agricultural crops inUkraine under conditions of environmental management requires the use of modern scientific approaches. The complexity of solving this problem lies in the lack
Publikováno v:
Наукові вісті КПІ; № 1 (2017): ; 48-53
Научные вести КПИ; № 1 (2017): ; 48-53
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 48-53
Научные вести КПИ; № 1 (2017): ; 48-53
Research Bulletin of the National Technical University of Ukraine "Kyiv Politechnic Institute"; № 1 (2017): Engineering; 48-53
Background. Development of automated diagnostic requires selection and improvement of appropriate machine learning methods, in particular multiclass recognition. Artificial Neural Networks (ANN) of various architecture are considered as an approach t