Continual learning and data analysis of time series data

Continual learning and data analysis of time series data

Time Series Data (TSD) has become the cornerstone of critical applications in various fields. However, temporal analysis faces a significant challenge called catastrophic forgetting, where previously acquired knowledge or skills are lost when learning new tasks. Therefore, this study aims to integra...

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Main Author: Ke, Tangxin
Other Authors: Soh Yeng Chai
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Engineering
Online Access:https://hdl.handle.net/10356/176923
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1769232024-05-24T15:44:02Z Continual learning and data analysis of time series data Ke, Tangxin Soh Yeng Chai School of Electrical and Electronic Engineering EYCSOH@ntu.edu.sg Engineering Time Series Data (TSD) has become the cornerstone of critical applications in various fields. However, temporal analysis faces a significant challenge called catastrophic forgetting, where previously acquired knowledge or skills are lost when learning new tasks. Therefore, this study aims to integrate continuous learning (CL) techniques to mitigate the phenomenon of catastrophic forgetting and enhance the model's capacity for processing TSD. Focusing on the Human Activity Recognition (HAR) problem, this study utilized a hybrid CNN-LSTM hybrid model as the baseline and explored a range of continuous learning techniques, including Experience Replay, Elastic Weight Consolidation (EWC) and Progressive Neural Network (PNN) etc. to show the effectiveness of CL. Bachelor's degree 2024-05-23T06:41:21Z 2024-05-23T06:41:21Z 2024 Final Year Project (FYP) Ke, T. (2024). Continual learning and data analysis of time series data. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176923 https://hdl.handle.net/10356/176923 en B1096-231 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
spellingShingle Engineering
Ke, Tangxin
Continual learning and data analysis of time series data
description Time Series Data (TSD) has become the cornerstone of critical applications in various fields. However, temporal analysis faces a significant challenge called catastrophic forgetting, where previously acquired knowledge or skills are lost when learning new tasks. Therefore, this study aims to integrate continuous learning (CL) techniques to mitigate the phenomenon of catastrophic forgetting and enhance the model's capacity for processing TSD. Focusing on the Human Activity Recognition (HAR) problem, this study utilized a hybrid CNN-LSTM hybrid model as the baseline and explored a range of continuous learning techniques, including Experience Replay, Elastic Weight Consolidation (EWC) and Progressive Neural Network (PNN) etc. to show the effectiveness of CL.
author2 Soh Yeng Chai
author_facet Soh Yeng Chai
Ke, Tangxin
format Final Year Project
author Ke, Tangxin
author_sort Ke, Tangxin
title Continual learning and data analysis of time series data
title_short Continual learning and data analysis of time series data
title_full Continual learning and data analysis of time series data
title_fullStr Continual learning and data analysis of time series data
title_full_unstemmed Continual learning and data analysis of time series data
title_sort continual learning and data analysis of time series data
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/176923
_version_ 1806059747075424256

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