Time series anomaly detection
Anomaly detection on time series data can be applied to many domains. It can be applied to machinery prognostics and health management (PHM) which is crucial to ensure a system’s reliability, increase operational safety and reduce maintenance cost. In this paper, anomaly detection is done on a...
Main Author: | Lek, Jie Kai |
---|---|
Other Authors: | Kwoh Chee Keong |
Format: | Final Year Project (FYP) |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175134 |
Similar Items
-
Anomaly detection in multivariate time series using ensemble method
by: Liu, Yanling
Published: (2022) -
Anomaly Detection in Fractal Time Series with LSTM Autoencoders
by: Kirichenko, Lyudmyla, et al.
Published: (2024) -
Machine learning for anomaly detection on intelligent transportation time series data
by: Lin, Yuxuan
Published: (2022) -
Leveraging large language models and BERT for log parsing and anomaly detection
by: Zhou, Yihan, et al.
Published: (2024) -
Wavelets meet transformers: an experimental approach to time series forecasting
by: Ng, Andrew Yong Kuan
Published: (2024)