Statistical Learning to Assess Overhead Line Lifespan

Authors :: Jean-Michel Ghidaglia
Fikri Hafid
Nicolas Vayatis
Christine Yang
V. Laurent
Mathilde Mougeot
Eurobios
CB - Centre Borelli - UMR 9010 (CB)
Service de Santé des Armées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-Université de Paris (UP)
RTE
Source :: Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018), Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018), Nov 2018, Dubrovnik, Croatia. 47 (5 pp.)-47 (5 pp.), ⟨10.1049/cp.2018.1879⟩
Publication Year :: 2018
Publisher :: HAL CCSD, 2018.
Abstract: International audience

Subjects :: Computer science
Statistical learning
business.industry
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Artificial intelligence
Machine learning
computer.software_genre
business
computer
Overhead line
ComputingMilieux_MISCELLANEOUS

Language :: English
Database :: OpenAIRE
Journal :: Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018), Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018), Nov 2018, Dubrovnik, Croatia. 47 (5 pp.)-47 (5 pp.), ⟨10.1049/cp.2018.1879⟩
Accession number :: edsair.doi.dedup.....7ef7d5760333a169d19f468e19087a05
Full Text :: https://doi.org/10.1049/cp.2018.1879⟩