Scientists Unveil the Most Realistic Black Hole Accretion Model Ever Created

Using cutting-edge algorithms and exascale supercomputers, researchers have created the most realistic simulations yet of matter flowing into black holes. Building on decades of research, a group of c ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
IEEE

Nonlinear Regression Models in Power System Optimization

Abstract: Strength system optimization is a challenging trouble, because it entails a couple of objectives, constraints, records, and variables. Historically, linear regression fashions including ...
Open Heart

Development and validation of a 10-year predictive model for cardiovascular and metabolic disease risk: insights from a large-scale health examination cohort

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...
Devdiscourse

Advanced AI system accurately forecasts ecological strain over three decades

Their study presents a new combination of computational tools that merges the Chinese Pangolin Optimizer (CPO) with the ...
GitHub

Nonlinear Regression: Estimating Hand-to-Camera Distance

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 ...
Frontiers

Developing a generalized nonlinear mixed-effects biomass model at stand-level under different age conditions for Chinese fir based on LiDAR and ground survey data in southern China

Introduction: Chinese fir (Cunninghamia lanceolata) is a crucial afforestation and timber species in southern China. Accurate estimation of its stand biomass is vital for forest resource assessment, ...
JSTOR Daily

Bayesian Analysis of Mixed-effect Regression Models Driven by Ordinary Differential Equations

Non-linear regression models with regression functions specified by ordinary differential equations (ODEs) involving some unknown parameters are used to model dynamical systems appearing in ...
Scientific Research Publishing

Discovering the Best Choice for Spline’s Knots and Intervals Using Order of Polynomial Regression Model ()

1 Department of Statistics, College of Arts and Science, University of Benghazi, Benghazi, Libya. 2 Department of Mathematics, College Arts and Science, University of Benghazi, Benghazi, Libya. 3 ...