Predicting the adhesive force between steel reinforcement and concrete is crucial as it influences stress distribution and the overall mechanical behavior of reinforced concrete. This study proposes a ...

Abstract: Bayesian optimization is commonly used to optimize black-box functions associated with simulations in engineering and science. Bayesian optimization contains two essential components: the ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

This repository contains experiment that implements Bayesian Optimization (BO) techniques for Conditional Value-at-Risk (CVaR)-based portfolio optimization, inspired by the research paper "Bayesian ...

Background and objective: The increasing global prevalence of diabetes has led to a surge in complications, significantly burdening healthcare systems and affecting patient quality of life. Early ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

Abstract: Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free ...

J. O. Lübsen, A. Eichler, "An Anlysis of Safety Guarantees in Multi-Task Bayesian Optimization" To run the proposed SaMSBO algorithm, the user can execute the 'run_samsbo.py' file. The remaining ...

ABSTRACT: The rapid prediction of aerodynamic performance is critical in the conceptual and preliminary design of hypersonic vehicles. This study focused on axisymmetric body configurations commonly ...