| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Fuzzy classification with restricted Boltzman machines and echo-state networks for predicting potential railway door system failures |
| Autor/-in: | Fink, Olga Zio, Enrico Weidmann, Ulrich |
| DOI: | 10.1109/TR.2015.2424213 |
| Erschienen in: | IEEE Transactions on Reliability |
| Band(Heft): | 64 |
| Heft: | 3 |
| Seite(n): | 861 |
| Seiten bis: | 868 |
| Erscheinungsdatum: | 2015 |
| Verlag / Hrsg. Institution: | IEEE |
| ISSN: | 0018-9529 1558-1721 |
| Sprache: | Englisch |
| Fachgebiet (DDC): | 004: Informatik 620: Ingenieurwesen |
| Zusammenfassung: | In this paper, a fuzzy classification approach applying a combination of Echo-State Networks (ESNs) and a Restricted Boltzmann Machine (RBM) is proposed for predicting potential railway rolling stock system failures using discrete-event diagnostic data. The approach is demonstrated on a case study of a railway door system with real data. Fuzzy classification enables the use of linguistic variables for the definition of the time intervals in which the failures are predicted to occur. It provides a more intuitive way to handle the predictions by the users, and increases the acceptance of the proposed approach. The research results confirm the suitability of the proposed combination of algorithms for use in predicting railway rolling stock system failures. The proposed combination of algorithms shows good performance in terms of prediction accuracy on the railway door system case study. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/13905 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
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Fink, O., Zio, E., & Weidmann, U. (2015). Fuzzy classification with restricted Boltzman machines and echo-state networks for predicting potential railway door system failures. IEEE Transactions on Reliability, 64(3), 861–868. https://doi.org/10.1109/TR.2015.2424213
Fink, O., Zio, E. and Weidmann, U. (2015) ‘Fuzzy classification with restricted Boltzman machines and echo-state networks for predicting potential railway door system failures’, IEEE Transactions on Reliability, 64(3), pp. 861–868. Available at: https://doi.org/10.1109/TR.2015.2424213.
O. Fink, E. Zio, and U. Weidmann, “Fuzzy classification with restricted Boltzman machines and echo-state networks for predicting potential railway door system failures,” IEEE Transactions on Reliability, vol. 64, no. 3, pp. 861–868, 2015, doi: 10.1109/TR.2015.2424213.
FINK, Olga, Enrico ZIO und Ulrich WEIDMANN, 2015. Fuzzy classification with restricted Boltzman machines and echo-state networks for predicting potential railway door system failures. IEEE Transactions on Reliability. 2015. Bd. 64, Nr. 3, S. 861–868. DOI 10.1109/TR.2015.2424213
Fink, Olga, Enrico Zio, and Ulrich Weidmann. 2015. “Fuzzy Classification with Restricted Boltzman Machines and Echo-State Networks for Predicting Potential Railway Door System Failures.” IEEE Transactions on Reliability 64 (3): 861–68. https://doi.org/10.1109/TR.2015.2424213.
Fink, Olga, et al. “Fuzzy Classification with Restricted Boltzman Machines and Echo-State Networks for Predicting Potential Railway Door System Failures.” IEEE Transactions on Reliability, vol. 64, no. 3, 2015, pp. 861–68, https://doi.org/10.1109/TR.2015.2424213.
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