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- W4385729592 abstract "Visible light communication (VLC) is an active and promising technology in the new world of wireless communications. Research has proved the importance of VLC technology shortly because of its ability to simultaneously illuminate and transmit data as it uses LEDs for transmission. However, the VLC channel sufferers from non-linearity, hence, this affects data transmission. On the other hand machine learning (ML) technology is known to solve non-linear problems. Therefore, the integration of the two technologies can drastically enhance the ability of VLC systems. In this research, three classification ML algorithm were employed in the system model. The performance of each ML algorithm is also analyzed, where the RF achieved a 97.4% prediction accuracy, and both the DT and SVM produced a 100% prediction accuracy. The system model design comprised of a MIMO indoor VLC system Matlab simulation, and a manual integration to the Python simulated ML algorithm." @default.
- W4385729592 created "2023-08-11" @default.
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- W4385729592 date "2023-07-18" @default.
- W4385729592 modified "2023-09-25" @default.
- W4385729592 title "Machine Learning Assisted Indoor Visible Light Communication System" @default.
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- W4385729592 doi "https://doi.org/10.1109/itc-egypt58155.2023.10206067" @default.
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