Proposed Long Short-Term Memory Model Utilizing Multiple Strands for Enhanced Forecasting and Classification of Sensory Measurements

Proposed Long Short-Term Memory Model Utilizing Multiple Strands for Enhanced Forecasting and Classification of Sensory Measurements

This paper presents a new deep learning model called the stranded Long Short-Term Memory. The model utilizes arbitrary LSTM recurrent neural networks of variable cell depths organized in classes. The proposed model can adapt to classifying emergencies at different intervals or provide measurement pr...

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Bibliographic Details
Main Authors: Sotirios Kontogiannis, George Kokkonis, Christos Pikridas
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Mathematics
Subjects:
deep learning
forecasting algorithms
classification algorithms
neural networks
recurrent neural networks
Online Access:https://www.mdpi.com/2227-7390/13/8/1263
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