A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...

In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...

Microsoft has added official Python support to Aspire 13, expanding the platform beyond .NET and JavaScript for building and running distributed apps. Documented today in a Microsoft DevBlogs post, ...

This project implements a quadratic nonlinear regression model to estimate the real-world distance between a hand and a camera based on the relative positions of hand landmarks in 2D images. The ...

Python has been the language of data science since before machine learning was trendy, and now you can use it for building AI agents, too. Get the scoop on the new Google Agent Development Kit and ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...

Department of Chemical Engineering, Imperial College London, London SW7 2AZ, U.K. Sargent Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ, U.K.

Chaotic systems, such as fluid dynamics or brain activity, are highly sensitive to initial conditions, making long-term predictions difficult. Even minor errors in modeling these systems can rapidly ...