Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series
Byeongcheon Lee, Sangmin Kim, Muazzam Maqsood, Jihoon Moon, Seungmin Rho
2024Computers, materials & continua/Computers, materials & continua (Print)11 citationsDOIOpen Access PDF
Abstract
In the context of rapid digitization in industrial environments, how effective are advanced unsupervised learning models, particularly hybrid autoencoder models, at detecting anomalies in industrial control system (ICS) datas... | Find, read and cite all the research you need on Tech Science Press
Topics & Concepts
AutoencoderAnomaly detectionMultivariate statisticsSeries (stratigraphy)Anomaly (physics)Time seriesComputer scienceArtificial intelligencePattern recognition (psychology)Machine learningDeep learningGeologyPhysicsCondensed matter physicsPaleontologyAnomaly Detection Techniques and ApplicationsTime Series Analysis and Forecasting