Consequently, this study explores, analyses and evaluates the application of global multi-objective Bayesian optimization for machine design. Employing four distinct Bayesian acquisition functions, ...

During the design of electrical machines, multiple performance objectives need to be considered. Although stochastic optimization algorithms are extensively employed for this purpose, a primary ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Process Optimization Problem In Multi-Objective Bayesian Optimization (MOBO), the goal is to find the optimal configuration of parameters (e.g., design parameters like color, transparency, and ...

Road traffic flow forecasting provides critical information for the operational management of road mobility challenges, and models are used to generate the forecast. This paper uses a random process ...

Flow electrosynthesis has attracted increasing attention as a green and sustainable manufacturing method. However, it is still a challenging undertaking to determine the appropriate experimental ...