This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
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 ...
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 ...
This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for addressing missing data in mine ventilation parameters. Using historical ventilation system data from ...
A simple treatment algorithm may help reduce treatment disparities for Hispanic and Black people with multiple sclerosis (MS), according to a preliminary study released today, March 3, 2025, that will ...
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