Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models like regression, dec ...
ABSTRACT: The solar data used to size installations for energy needs are most often oversized. The data used are either old or suffer from the effects of climate change or from data extrapolated to a ...
Abstract: Mixed linear regression (MLR) models nonlinear data as a mixture of linear components. When noise is Gaussian, the Expectation-Maximization (EM) algorithm is commonly used for maximum ...
The goal of liu.lab4.algorithms is to provide an R implementation of a multiple linear regression mode. This package was created for Lab 4 in the course 732A94 Advanced R Programming at Linköping ...
ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...
Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...
Abstract: This paper investigates the optimization of the co-pyrolysis process of biomass and coal, aiming to enhance tar yield and energy conversion efficiency. Initially, we conducted preprocessing ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results