Tech Xplore

Compression technique makes AI models leaner and faster while they're still learning

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...

Machine learning tracks methane emissions from orbit

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...
Morning Overview on MSN

New AI model aims to improve seasonal drought forecasts

Federal scientists announced a new artificial intelligence tool that can forecast drought conditions 90 days ahead across the ...
EurekAlert!

Automotive sector accelerates carbon footprint reduction with advanced AI and cloud framework

A team of researchers presents a novel interdisciplinary strategy to tackle the complex challenge of Scope 3 emissions within ...

Unlocking subsurface geoenergy and storage potential using machine learning

FAYETTEVILLE, GA, UNITED STATES, March 20, 2026 /EINPresswire.com/ -- Using machine learning regression models, we ...
GitHub

CheeseThuong/Predicting-water-levels-using-Linear-Regression

This project addresses the problem of predicting water levels in fish ponds - a critical factor in aquaculture management. Using Machine Learning, we can: Predict water levels based on environmental ...
IEEE

The Impact of Feature Scaling in Machine Learning: Effects on Regression and Classification Tasks

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...
GitHub

AI-Based Inference System for Concrete Compressive Strength: Multi-dataset Analysis of Optimized Machine Learning Algorithms

The prediction of concrete compressive strength (CS, MPa) is fundamental in experimental civil engineering, as it enables the optimization of mix design and complements laboratory testing through ...
EurekAlert!

Transforming acute exacerbations of chronic obstructivepulmonary disease (AECOPD) risk assessment: Amulti-algorithm machine learning approach for preciseclinical phenotyping

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...
ascopubs.org

Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States

This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...
Scientific Research Publishing

Hope, T. M. H. (2020). Linear Regression. In A. Mechelli, & S. Vieira (Eds.), Machine Learning (pp. 67-81). Elsevier.

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
Scientific Research Publishing

Maulud, D., & Abdulazeez, A. M. (2020). A Review on Linear Regression Comprehensive in Machine Learning. Journal of Applied Science and Technology Trends, 1, 140-147.

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...