The parallel efficient global optimization (EGO) algorithm was developed to leverage the rapid advancements in high-performance computing. However, conventional parallel EGO algorithm based on ...

A software engineer and book author with many years of experience, I have dedicated my career to the art of automation. A software engineer and book author with many years of experience, I have ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

SLSQP stands for Sequential Least Squares Programming. It is a numerical optimization algorithm used to solve constrained nonlinear optimization problems. In this project, we aim to optimize objective ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. A rapid and sensitive segmented gradient elution high-performance liquid ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

When using matplotlib, plotnine, or other Python plotting libraries, clearing plots in the plot pane does not work as expected. Previously cleared plots may reappear, and some earlier plots remain ...

Abstract: This paper presents an extended gradient-based optimization framework for optimal control problems governed by general conformable fractional derivatives (GCFDs), which unify various ...

Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for improving optimization techniques in machine learning! 💡🔧 #NesterovGradient ...