Autoencoder-Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm

Autoencoder-Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm

This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become increasingly important due to growing availability in many industrial fields. Labelin...

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Bibliographic Details
Main Authors: Jonas Kohne, Lars Henning, Clemens Guhmann
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Condition-based maintenance
multivariate time-series data
change point detection
unsupervised clustering
autoencoder
segmentation
Online Access:https://ieeexplore.ieee.org/document/10049550/

Internet

https://ieeexplore.ieee.org/document/10049550/

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