Optimized memory allocation in edge-PLCs using Deep Q-Networks and bidirectional LSTM with Quantum Genetic Algorithm

Optimized memory allocation in edge-PLCs using Deep Q-Networks and bidirectional LSTM with Quantum Genetic Algorithm

This paper offers a fresh perspective to memory allocation in edge-PLCs within industrial IoT environments, leveraging a hybrid a structure that incorporates Deep Q-Networks (DQN) and Bidirectional Long Short-Term Memory Networks (BiLSTM), complemented by Quantum Genetic Algorithm Optimization. In a...

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Bibliographic Details
Main Authors: N. Naveen Kumar, S. Saravana, S. Balamurugan, P. Seshu Kumar, S. Suresh
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:e-Prime: Advances in Electrical Engineering, Electronics and Energy
Subjects:
Reinforcement learning
Memory allocation
Edge-PLCs
BiLSTM networks
Quantum Genetic Algorithm Optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2772671124003425
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