Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Kerelous Waghen"'
Autor:
Kerelous Waghen, Mohamed-Salah Ouali
Publikováno v:
Algorithms, Vol 15, Iss 6, p 178 (2022)
This paper develops a data-driven fault tree methodology that addresses the problem of the fault prognosis of an aging system based on an interpretable time causality analysis model. The model merges the concepts of knowledge discovery in the dataset
Externí odkaz:
https://doaj.org/article/1af179382beb4fe2beb89d59cc46c603
Autor:
Mohamed-Salah OUALI, Kerelous Waghen
Publikováno v:
Algorithms; Volume 15; Issue 6; Pages: 178
This paper develops a data-driven fault tree methodology that addresses the problem of the fault prognosis of an aging system based on an interpretable time causality analysis model. The model merges the concepts of knowledge discovery in the dataset
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::056cefa3fe67c6b8caf60513630d7874
Autor:
Mohamed-Salah Ouali, Kerelous Waghen
Publikováno v:
Expert Systems with Applications. 136:376-391
This paper proposes an effective hybrid-based methodology, called interpretable logic tree analysis (ILTA), which characterizes and quantifies event causality occurring in engineering systems with the minimum involvement of human experts. It integrat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71873f5a4824dc8c873e8d6576ada45f
https://doi.org/10.1016/j.eswa.2019.06.042
https://doi.org/10.1016/j.eswa.2019.06.042