An interpretable unsupervised Bayesian network model for fault detection and diagnosis - Mines Saint-Étienne
Journal Articles Control Engineering Practice Year : 2022

An interpretable unsupervised Bayesian network model for fault detection and diagnosis

Domains

Machine Learning [stat.ML] Artificial Intelligence [cs.AI]

Valeria Borodin  : Connect in order to contact the contributor

https://hal-emse.ccsd.cnrs.fr/emse-03754041

Submitted on : Friday, August 19, 2022-9:59:06 AM

Last modification on : Tuesday, September 17, 2024-3:45:01 PM

No file

Dates and versions

emse-03754041 , version 1 (19-08-2022)

Identifiers

Cite

Wei-Ting Yang, Marco Reis, Valeria Borodin, Michel Juge, Agnès Roussy. An interpretable unsupervised Bayesian network model for fault detection and diagnosis. Control Engineering Practice, 2022, 127, pp.105304. ⟨10.1016/j.conengprac.2022.105304⟩. ⟨emse-03754041⟩

Export

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

EMSE PRES_CLERMONT CNRS LIMOS CLERMONT-AUVERGNE-INP INSTITUT-MINES-TELECOM
85 View
0 Download

Altmetric

Share

More