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/

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