- Pattern recognition for predictive analysis in automotive industry
Number of the records: 1  

Pattern recognition for predictive analysis in automotive industry

  1. CREPC201709 CREPC201710 CREPC201711 CREPC022018 CREPC201802 CREPC201803 CREPC201806
    Title statementPattern recognition for predictive analysis in automotive industry / aut. Veronika Šimončičová, Lukáš Hrčka, Lukáš Špendla, Pavol Tanuška, Pavel Važan
    Main entry-name Šimončičová, Veronika, 1991- (Author) - MTF Ústav aplikovanej informatiky, automatizácie a mechatroniky
    Another responsib. Hrčka, Lukáš, 1989- Z3 (Author) - MTF Ústav aplikovanej informatiky, automatizácie a mechatroniky
    Špendla, Lukáš, 1984- Z1 (Author) - MTF Ústav aplikovanej informatiky, automatizácie a mechatroniky
    Tanuška, Pavol, 1966- Z1 (Author) - MTF Ústav aplikovanej informatiky, automatizácie a mechatroniky
    Važan, Pavel, 1962- Z1 (Author) - MTF Ústav aplikovanej informatiky, automatizácie a mechatroniky
    In Cybernetics and mathematics applications in intelligent systems [448 s.] / Computer science on-line conference. -- Cham : Springer International Publishing AG, 2017. -- ISBN 978-3-319-57263-5. -- ISSN 2194-5357. -- S. 311-318
    Subj. Headings automotive industry
    intelligent system
    maintenance
    LanguageEnglish
    Document kindRZB - článok zo zborníka
    CategoryAFC - Reports at international scientific conferences
    Category (from 2022)V2 - Vedecký výstup publikačnej činnosti ako časť editovanej knihy alebo zborníka
    Year2017
    Citations [1] 2018: RAVI, Vidya - PATIL, Ravindra. Unsupervised time series data analysis for error pattern extraction for predictive maintenance. In Communications in Computer and Information Science, 2018, 906, pp. 1-10. ISSN 18650929.
    [1] 2021: SRINIVASAN, R. - MANIVANNAN, S. - PRASANNA DEVI, S. - NALLUSAMY, S. - ETHIRAJ, N. Predictive analysis of time to failure for sustainable development in an automobile component manufacturing industry. In Journal of Green Engineering, 2021, 11, 2, pp. 1088-1105. ISSN 19044720.
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Number of the records: 1  

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