Abstract: Duringthe design of electrical machines, multiple performance objectives need to be considered. Although stochastic optimization algorithms are extensively employed for this purpose, a ...
Users are more prepared to buy than ever before when they arrive at your site from an answer engine. The answer engine optimization industry has been infected by a terrible disease of terms that don’t ...
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 ...
In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...
Olivera Ciraj Bjelac, IAEA Department of Nuclear Sciences and Applications To support hospitals and specialists around the world in meeting their safety standards requirements, the IAEA has produced a ...
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 ...
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 ...
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 ...
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