Anomaly Detection Paradigm for Multivariate Time Series Data Mining for Healthcare

Anomaly Detection Paradigm for Multivariate Time Series Data Mining for Healthcare

Time series data are significant, and are derived from temporal data, which involve real numbers representing values collected regularly over time. Time series have a great impact on many types of data. However, time series have anomalies. We introduce an anomaly detection paradigm called novel matr...

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Bibliographic Details
Main Authors: Abdul Razaque, Marzhan Abenova, Munif Alotaibi, Bandar Alotaibi, Hamoud Alshammari, Salim Hariri, Aziz Alotaibi
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
time series
NMP
anomalies
data mining
similarities in time series
clustering
Online Access:https://www.mdpi.com/2076-3417/12/17/8902

Internet

https://www.mdpi.com/2076-3417/12/17/8902

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