Zimovets V. Models, methods and information technology of functional diagnostics of multichannel mine lifting machine

Українська версія

Thesis for the degree of Candidate of Sciences (CSc)

State registration number

0421U101075

Thesis Registration Form

0421U101075.pdf

Applicant for

Specialization

  • 05.13.06 - Інформаційні технології

21-04-2021

Specialized Academic Board

Д 64.050.07

National Technical University "Kharkiv Polytechnic Institute"

Essay

The dissertation is devoted to increase of functional efficiency of the system of functional diagnostics of a multichannel mine lifting machine by creation of information technology of machine learning. The object of the study is a poorly formalized machine learning process of functional diagnostics system with incomplete data definiteness caused by arbitrary initial conditions of technological cycle and intersection in the space of features of recognition classes that characterize the technical condition of nodes and devices of a multi-wire mine machine. The subject of research are models and methods of information technology of functional efficiency estimation and optimization of parameters capable of learning the system of functional diagnostics of multi-wire mine lifting machine.

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Files

autoreferat-avtoreferat_2021_Zymovets_Modeli_metody.pdf

дисертація_Зимовець_15.03.docx

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