In microbiome studies, addressing the unique characteristics of sequence data—such as compositionality, zero inflation, overdispersion, high dimensionality, and non-normality—is crucial for accurate ...

Understanding brain—behavior relationships and predicting cognitive and clinical outcomes from neuromarkers are central tasks in neuroscience. Connectome-based Predictive Modeling (CPM) has been ...

ABSTRACT: This study presents the Dynamic Multi-Objective Uncapacitated Facility Location Problem (DMUFLP) model, a novel and forward-thinking approach designed to enhance facility location decisions ...

This study demonstrates the first successful construction of a fluid model that captures both kinetic Landau damping and Bernstein modes through precise rational approximations and transformation into ...

Abstract: In this paper a generalized net model of the Deep Learning Neural Network Algorithm (DLNNA) is presented. A DLNN is a self-organizing network with the ability to recognize patterns based on ...

Abstract: This paper presents an autoML algorithm to select linear regression model and its performance evaluation for any linear dataset. It computes and compares the performance of various multiple ...

ABSTRACT: This study investigates the impact of marketing mix elements—Product, Price, Promotion, and Place (4Ps)—on the revenue and profit of Nigerian Breweries Plc (NBL) from 2013 to 2022, using ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...