Intelligent automated computer systems

dc.contributor.authorZakovorotniy, Alexandr
dc.contributor.authorKharchenko, Artem
dc.date.accessioned2024-11-14T12:32:16Z
dc.date.issued2021
dc.description.abstractFuzzy logic and neural network methods are currently used to solve problems related to process modeling in the conditions of uncertainty or insufficient input data. Neural networks allow not only to model processes as close as possible to real ones, but also to forecast the values of technical parameters. The reliability of a computer system depends on the right choice of the input parameters and the accuracy of calculations. This work is devoted to the issue of developing the automated computer system, taking into account the dynamics of railway vehicles.
dc.identifier.citationZakovorotniy A. Yu. Intelligent automated computer systems Alexandr Zakovorotniy, Artem Kharchenko [Electronic resource] // Information Technologies And Management : theses of the 19ᵗʰ Intern. conf., April 22-23, 2021. – Electronic text data. – Riga, Latvia : ISMA University of Applied Science, 2021. – Р. 114. – URL: https://ismaitm.lv/conference-2021/, (accessed 14.11.2024).
dc.identifier.urihttps://repository.kpi.kharkov.ua/handle/KhPI-Press/83423
dc.language.isoen
dc.publisherInformacijas Sistemu Menedžmenta Augstskola
dc.subjectcomputer systems
dc.subjectfuzzy logic
dc.subjectneural network
dc.subjectintelligent control
dc.subjectforecasting
dc.titleIntelligent automated computer systems
dc.typeArticle

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