• Vitoria Jesuremen Anthony
• Adeyinka Taye Iyinoluwa
• Adeyinka Kehinde Iyioluwa
• Ameer Ali Fadhil Fadhil

Backgound: In this paper, we propose artificial intelligent feedback-controlled adaptive particle swarm optimization (AI-FC-APSO) algorithm specifically using neural network for optimizing the placement of a re-configurable intelligent surface (RIS) in a visible light communication (VLC) system operating under variable lighting conditions. Unlike traditional optimization methods, the proposed AI-FC-APSO dynamically adjusts the RIS configuration in response to changes in ambient light intensity (γ), maintaining high signal-to-noise ratio (SNR) and minimizing bit error rate (BER) using artificial intelligent feedback mechanisms specifically neural network are integrated to monitor the search process and adjust parameters in real-time of original FC-APSO. This feedback can be based on various factors like the convergence rate, diversity of the swarm, or the success of individual particles. We further evaluate the system’s energy efficiency (EE), showing that the proposed method not only improves performance but also reduces power consumption. Comparative analysis with genetic algorithms (GA), static RIS placement, and standard PSO demonstrates that AI-FC-APSO achieves superior robustness and efficiency, especially under fluctuating illumination. Simulation results show that AI-FC-APSO maintains SNR levels above 90 dB and BER below 10⁻⁹ across a wide range of lighting conditions, making it a promising solution for real-time VLC applications.

VLC, Reconfigurable Intelligent Surface, Energy Efficiency, SNR, BER, Particle Swarm Optimization, AI-FC-APSO, Adaptive Communication

"Implementation of artificial intelligent using feedback-controlled adaptive particle swarm optimization (AI-FC-APSO) for reconfigurable intelligent surface (RIS) in a visible light communication (VLC) system", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.d758-d763, September-2025, Available :http://www.jetir.org/papers/JETIR2509398.pdf

"Implementation of artificial intelligent using feedback-controlled adaptive particle swarm optimization (AI-FC-APSO) for reconfigurable intelligent surface (RIS) in a visible light communication (VLC) system", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppd758-d763, September-2025, Available at : http://www.jetir.org/papers/JETIR2509398.pdf