Multivariate Time Series Data Generation using Generative Adversarial Networks : Generating Realistic Sensor Time Series Data of Vehicles with an Abnormal Behaviour using TimeGAN

Multivariate Time Series Data Generation using Generative Adversarial Networks : Generating Realistic Sensor Time Series Data of Vehicles with an Abnormal Behaviour using TimeGAN

Large datasets are a crucial requirement to achieve high performance, accuracy, and generalisation for any machine learning task, such as prediction or anomaly detection, However, it is not uncommon for datasets to be small or imbalanced since gathering data can be difficult, time-consuming, and exp...

Full description

Bibliographic Details
Main Author: Nord, Sofia
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Time Series Data Generation
Generative Adversarial Network
Deep Neural Network
Data Augmentation
Synthetic Data Generation
Generering av Tidsseriedata
Generativa Motstridande Nätverk
Djupa Neurala Nätverk
Dataökning
Syntetisk Datagenerering
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302644

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302644

Similar Items