Training the Recurrent neural network by the Fuzzy Min-Max algorithm for fault prediction

Ryad Zemouri (1) , Daniel Racoceanu (2) , Noureddine Zerhouni (3, 4) , Eugénia Minca (5) , Florin Gheorghe Filip (6)

1 CEDRIC - LAETITIA - CEDRIC. Traitement du signal et architectures électroniques
2 IPAL - Image & Pervasive Access Lab
3 LAB - Laboratoire d'automatique de Besançon
4 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)
5 UVT - Valahia University of Targoviste [Roumanie]
6 Romanian Academy

Domains: Machine Learning [cs.LG]

Ryad Zemouri, Daniel Racoceanu, Noureddine Zerhouni, Eugénia Minca, Florin Gheorghe Filip. Training the Recurrent neural network by the Fuzzy Min-Max algorithm for fault prediction. Intelligent systems and automation: 2nd Mediterranean Conference on Intelligent Systems and Automation (CISA’09), Mar 2009, Zarzis (Tunisia), France. pp.85-90, ⟨10.1063/1.3106518⟩. ⟨hal-02479235⟩