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Extreme-Long-short term memory for Time-series Prediction

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thesis
posted on 2024-10-10, 00:26 authored by Sida Xing
This thesis introduces a novel neural network, the Extreme Long Short-Term Memory (E-LSTM), combine the advantages of Long Short-Term Memory (LSTM) networks and Extreme Learning Machines (ELM). Empirical evidence demonstrates that E-LSTM significantly bolsters computational efficiency, concurrently maintaining a high prediction accuracy.

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Pagination

70 p.

Open access

  • Yes

Language

eng

Degree type

Master

Degree name

MEng

Copyright notice

All rights reserved

Editor/Contributor(s)

Sui Yang Khoo, Michael Norton

Faculty

Faculty of Science, Engineering and Built Environment

School

School of Engineering

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