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

Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e)

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Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Industrial Engineering and Innovation Sciences
Supervisors/Advisors	Kaymak, Uzay, Promotor Zhang, Yingqian, Copromotor Akcay, A.E., Copromotor
Award date	3 Feb 2022
Place of Publication	Eindhoven
Publisher	Eindhoven University of Technology
Print ISBNs	978-90-386-5430-0
Publication status	Published - 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",

}