Open Access Journal of Engineering Applications
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Bayesian Optimization Applied to 5G Network Slicing

Layla Roy Corresponding 0000-0002-7948-8754
King Abdullah University of Science and Technology
Chen Uddin 0000-0002-7599-2565
University of Dhaka
31 Mar 2026
pp. 701-721
https://doi.org/10.55555/oajea.2026.5001.032

Abstract

Accurate prediction of 5G network slicing is essential for the design, operation, and maintenance of urban transportation networks. The performance of Bayesian optimization was evaluated using standard error metrics and cross-validation. The optimized design achieved a 43% improvement in efficiency over the reference case. The outcomes point to clear priorities for further experimental and field investigation.
Keywords: 5G network slicingBayesian optimizationrenewable energyflood forecastinggenetic algorithmenergy efficiency

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