Abstract: Under the background of the era of artificial intelligence, predicting product demand through machine learning can effectively improve the production and sales benefits of enterprises. Based ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In this paper, we introduce a methodology to improve upon the ...

This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Multi-Objective Bayesian Optimization (MOBO) workflow built on botorch.org. It lets you declare design parameters and objectives in ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

ABSTRACT: The rapid proliferation of the Internet of Things (IoT) and Industrial IoT (IIoT) has revolutionized industries through enhanced connectivity and automation. However, this expansion has ...

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 ...

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 ...

Next to the primary optimization objectives, scientific optimization problems often contain a series of subordinate objectives, which can be expressed as preferences over either the outputs of an ...