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pro vyhledávání: '"Bektas, Oguz"'
Autor:
Bektas, Oguz
The field of Prognostics and Health Management is becoming ever more important in the modern maintenance era, with advanced techniques of automation and mechanisation becoming increasingly prevalent. Prognostic technology has promising abilities to f
Externí odkaz:
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.752514
Autor:
Ozkat, Erkan Caner1,2 erkancaner.ozkat@erdogan.edu.tr, Bektas, Oguz3, Nielsen, Michael Juul1, la Cour-Harbo, Anders1
Publikováno v:
International Journal of Micro Air Vehicles. Jan-Dec2023, Vol. 15, p1-14. 14p.
Autor:
Bektas, Oguz1 o.bektas@warwick.ac.uk, Jones, Jeffrey A.1 J.A.Jones@warwick.ac.uk, Sankararaman, Shankar2 shankar.sankararaman@pwc.com, Roychoudhury, Indranil3 indranil.roychoudhury@nasa.gov, Goebel, Kai4,5 kai.goebel@nasa.gov
Publikováno v:
International Journal of Advanced Manufacturing Technology. Mar2019, Vol. 101 Issue 1-4, p87-103. 17p.
Akademický článek
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Autor:
Bektas, Oguz ⁎, Jones, Jeffrey A., Sankararaman, Shankar, Roychoudhury, Indranil, Goebel, Kai
Publikováno v:
In MethodsX 2019 6:383-390
Publikováno v:
In Data in Brief December 2018 21:2464-2469
Publikováno v:
Journal of Failure Analysis & Prevention; Dec2017, Vol. 17 Issue 6, p1268-1275, 8p
Autor:
Bektas, Oguz
The field of Prognostics and Health Management is becoming ever more important in the modern maintenance era, with advanced techniques of automation and mechanisation becoming increasingly prevalent. Prognostic technology has promising abilities to f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::f7089bac5c93b157ea9c74e557f46ab2
http://wrap.warwick.ac.uk/106052/1/WRAP_Theses_Bektas_2018.pdf
http://wrap.warwick.ac.uk/106052/1/WRAP_Theses_Bektas_2018.pdf
Autor:
Bektas, Oguz, Jones, Jeffrey Alun
Publikováno v:
Third European Conference of the Prognostics and Health Management Society 2016
Prognostics is a promising approach used in condition based maintenance due to its ability to forecast complex systems' remaining useful life. In gas turbine maintenance applications, data-driven prognostic methods develop an understanding of system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::5d248d41632c204244243adc766d5be8
http://wrap.warwick.ac.uk/95585/7/WRAP-NARX-time-series-model-remaining-gas-engines-Bektas-2017.pdf
http://wrap.warwick.ac.uk/95585/7/WRAP-NARX-time-series-model-remaining-gas-engines-Bektas-2017.pdf