Analysis of neural network training algorithms for implementation of the prescriptive maintenance strategy
Authors:
- Paweł Lempa,
- Grzegorz Filo
Abstract
This paper presents a proposal to combine supervised and semi-supervised training strategies to obtain a neural network for use in the prescriptive maintenance approach. It is required in this approach because of only partially labelled data for use in supervised learning, and additionally, this data is predicted to expand quickly. The main issue is the decision on which are suitable training methodologies for supervised learning, having in mind using this data and methods for semi-supervised learning. The proposed methods of training neural networks with supervised and semi-supervised training to receive the best results will be tested and compared in further work.
- Record ID
- CUTf2e5f0d0b1b440368184c0f732192b14
- Publication categories
- ; ;
- Author
- Pages
- 281-287
- Other elements of collation
- rys.; Bibliografia (na s.) - 285-287; Bibliografia (liczba pozycji) - 37; Oznaczenie streszczenia - Abstr.
- Substantive notes
- Punktacja MNiSW/MEiN (rozdział) - 5
- Book
- Radek Norbert Norbert Radek (eds.): Terotechnology XII : 12th Conference on Terotechnology, 20-21 October 2021, Kielce, Poland, Materials Research Proceedings, no. 24, 2022, Millersville, PA, Materials Research Forum LLC, ISBN 978-1-64490-204-2 (print)
- Keywords in English
- neural network training, multilayer network training, supervised training, semi-supervised training, prescriptive maintenance
- DOI
- DOI:10.21741/9781644902059-41 Opening in a new tab
- URL
- https://doi.org/10.21741/9781644902059-41 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 20
- Score source
- journalList
- Score
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTf2e5f0d0b1b440368184c0f732192b14/
- URN
urn:pkr-prod:CUTf2e5f0d0b1b440368184c0f732192b14
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.