Title | ||
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A Deep Learning Based Explainable Control System for Reconfigurable Networks of Edge Devices |
Abstract | ||
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Edge devices that operate in real-world environments are subjected to unpredictable conditions caused by environmental forces such as wind and uneven surfaces. Since most edge systems such as autonomous vehicles exhibit dynamic properties, it is clear that reinforcement learning can be a powerful tool for improving system accuracy. Successful maintenance of the position of a vehicle in such enviro... |
Year | DOI | Venue |
---|---|---|
2022 | 10.1109/TNSE.2021.3083990 | IEEE Transactions on Network Science and Engineering |
Keywords | DocType | Volume |
Time series analysis,Data analysis,Biological system modeling,Reinforcement learning,Data models,Force,Vehicle dynamics | Journal | 9 |
Issue | ISSN | Citations |
1 | 2327-4697 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Priyanthi M. Dassanayake | 1 | 0 | 0.34 |
Ashiq Anjum | 2 | 0 | 0.34 |
Ali Kashif Bashir | 3 | 4 | 2.41 |
Joseph Bacon | 4 | 0 | 0.34 |
Rabia Saleem | 5 | 0 | 0.34 |
Warren Manning | 6 | 0 | 0.34 |