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A soft computing algorithmic technique for circuital analysis of a wireless mobile charger

Olukayode Ojo, AdedayoOladipupo Alegbeleye, OluwafemiOmowunmi Olomowewe, Rashida
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 Juni 2024
DOI10.11591/ijai.v13.i2.pp1443-1449

Abstrak

Wireless energy transfer is emerging as a promising technology for mobile devices because it enhances rapid charging without requiring conventional cables. In this paper, a wireless mobile charger circuit was designed and simulated, the data obtained thereof was used to train an artificial neural network (ANN) using Levenberg-Marquardt (LM) algorithm. The result obtained was validated against that obtained when trained with regular scaled conjugate algorithm. Analysis of the results showed that the proposed technique remains a viable technique for rapidly analyzing several parts of the wireless mobile charger circuit for design and educational purposes, without always executing computationally intensive and time-consuming simulations.

Kata Kunci

Artificial neural networkLevenberg-Marquardt algorithmWireless chargingWireless energy transferWireless rechargeable network

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A soft computing algorithmic technique for circuital analysis of a wireless mobile charger | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora