Tool condition monitoring (TCM) during mechanical cutting is critical for maximising the
utilisation of cutting tools and minimising the risk of equipment damage and personnel …

Bayesian optimization (BO) based on Gaussian process regression (GPR) is applied to
different CFD (computational fluid dynamics) problems which can be of practical relevance …

Bayesian optimization (BO) with Gaussian processes (GPs) surrogate models is widely used
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …

Abstract In Economic Development, human capital was previously seen as production
factors but gradually evolved into endogenous growth theories. Most of the previous studies …

This tutorial focuses on kriging-based simulation optimization, emphasizing the importance
of data efficiency in optimization problems involving expensive simulation models. It …

Cervical cancer is the most prevailing woman illness globally. Since cervical cancer is a very
preventable illness, early diagnosis exhibits the most adaptive plan to lessen its global …

Since soil temperature (ST) is one of the most critical determinants affecting the soil's
physical and chemical properties, the studies on soil temperature estimation increase with …

This study presents the efficacy of deep learning techniques in controlling the arm of a
humanoid robot without resorting to inverse kinematic analysis. Emphasizing real-time …

In recent years, various kinds of optimal design approaches are intensively studied for
exploring novel and higher performance microwave and optical devices beyond human …

This paper introduces an adaptive Bayesian optimization (BayesOpt) framework with
dynamic conditioning and jitter mechanisms. The new framework enhances the adaptability …