In production engineering, the identification of optimal process parameters is essential to advance product quality and overall equipment effectiveness. Optimizing and adapting process parameters ...

Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...

In today’s information-driven society, there’s an ever-increasing preference to measure phenomena such as temperature, pressure, light, force, voltage and current. These measurements can be used in a ...

When we first land in the Codex environment, it feels like stepping into a co-pilot’s seat for coding. Codex is designed to take over much of the routine or overwhelming parts of software engineering, ...

AI-powered search is drastically changing the way people find information. For years, ranking well in Google and Microsoft Bing has been the foundation of search visibility. But as AI-driven search ...

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 ...

The rapid advancement of Large Language Models (LLMs) has significantly improved their ability to generate long-form responses. However, evaluating these responses efficiently and fairly remains a ...

Abstract: This study proposes a Bayesian optimization-based diagnostic algorithm for convolutional neural networks (CNN), which improves the predictive performance of the model by optimizing the ...