HYBRID AUTOENCODER-ISOLATION FOREST APPROACH FOR TIME SERIES ANOMALY DETECTION IN C70XP CYCLOTRON OPERATION DATA AT ARRONAX
Authors
François Haddad (ORCID: https://orcid.org/0000-0002-9648-7671)
D Mateus
F Poirier
F Basbous
Institutions
École Centrale de Nantes (FR)
Centre National de la Recherche Scientifique (FR)
Montpellier GenomiX (FR)
Laboratoire de Physique Subatomique et des Technologies Associées (FR)
Laboratoire des Sciences du Numérique de Nantes (FR)
IMT Atlantique (FR)
Nantes Université (FR)
Publication Details
Journal
SPIRE - Sciences Po Institutional REpository
Published
2025-10-27
Primary Topic
Traffic Prediction and Management Techniques
Type
article
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article
HYBRID AUTOENCODER-ISOLATION FOREST APPROACH FOR TIME SERIES ANOMALY DETECTION IN C70XP CYCLOTRON OPERATION DATA AT ARRONAX
François Haddad, D Mateus, F Poirier, F Basbous
Journal
SPIRE - Sciences Po Institutional REpository
Topics
Traffic Prediction and Management Techniques
article
HYBRID AUTOENCODER-ISOLATION FOREST APPROACH FOR TIME SERIES ANOMALY DETECTION IN C70XP CYCLOTRON OPERATION DATA AT ARRONAX
François Haddad, D Mateus, F Poirier, F Basbous
article en
Abstract
No abstract available for this paper.
Publication Tag
SPIRE - Sciences Po Institutional REpository
Institutions
École Centrale de Nantes (FR), Centre National de la Recherche Scientifique (FR), Montpellier GenomiX (FR), Laboratoire de Physique Subatomique et des Technologies Associées (FR), Laboratoire des Sciences du Numérique de Nantes (FR), IMT Atlantique (FR), Nantes Université (FR)