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Journal Articles
- 2023
[j1]Minh-Huong Le Nguyen
, Fabien Turgis, Pierre-Emmanuel Fayemi, Albert Bifet:
Exploring the potentials of online machine learning for predictive maintenance: a case study in the railway industry. Appl. Intell. 53(24): 29758-29780 (2023)
Conference and Workshop Papers
- 2023
- [c6]Pietro Folco, Abderrahim Sahli, Sana Belmokhtar Berraf, Laurent Bouillaut, Pierre-Emmanuel Fayemi, Fabien Turgis:
An ILP for scheduling rolling stock maintenance activities under operational and logistical constraints. CoDIT 2023: 1313-1318 - 2022
- [c5]Minh-Huong Le Nguyen, Fabien Turgis, Pierre-Emmanuel Fayemi, Albert Bifet:
Continuous Health Monitoring of Machinery using Online Clustering on Unlabeled Data Streams. IEEE Big Data 2022: 1866-1873 - 2020
- [c4]Minh-Huong Le Nguyen, Fabien Turgis, Pierre-Emmanuel Fayemi, Albert Bifet:
Challenges of Stream Learning for Predictive Maintenance in the Railway Sector. IoT Streams/ITEM@PKDD/ECML 2020: 14-29 - 2019
- [c3]Giacomo Bersano, Pierre-Emmanuel Fayemi:
Application of TRIZ and Innovation Management Theory on Decision Support for Transport Infrastructure. TFC 2019: 486-493 - 2018
- [c2]Davide Russo, Pierre-Emmanuel Fayemi, Matteo Spreafico, Giacomo Bersano:
Design Entity Recognition for Bio-inspired Design Supervised State of the Art. TFC 2018: 3-13 - [c1]Pierre-Emmanuel Fayemi, Martin Gilles, Claude Gazo:
Innovative Technical Creativity Methodology for Bio-Inspired Design. TFC 2018: 253-265
Coauthor Index
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