Data-driven prognostics and logistics optimisation: A deep learning journey

Onderzoeksoutput: Scriptie › Dissertatie 1 (Onderzoek TU/e / Promotie TU/e)

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Originele taal-2	Engels
Kwalificatie	Doctor in de Filosofie
Toekennende instantie	Industrial Engineering and Innovation Sciences
Begeleider(s)/adviseur	Kaymak, Uzay, Promotor Zhang, Yingqian, Co-Promotor Akcay, A.E., Co-Promotor
Datum van toekenning	3 feb. 2022
Plaats van publicatie	Eindhoven
Uitgever	Eindhoven University of Technology
Gedrukte ISBN's	978-90-386-5430-0
Status	Gepubliceerd - 3 feb. 2022

Proefschrift.

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@phdthesis{1f15f37f41434b6799cce306bbff552f,

title = "Data-driven prognostics and logistics optimisation: A deep learning journey",

author = "\{de Oliveira da Costa\}, \{Paulo Roberto\}",

note = "Proefschrift.",

year = "2022",

month = feb,

day = "3",

language = "English",

isbn = "978-90-386-5430-0",

series = "SIKS Dissertation Series",

publisher = "Eindhoven University of Technology",

type = "Phd Thesis 1 (Research TU/e / Graduation TU/e)",

school = "Industrial Engineering and Innovation Sciences",

}