Tech Xplore

Computational 'time machine' shows solar and wind power on track for 2°C target, but not for 1.5°C

Wind and solar power have grown faster than almost anyone predicted, but projecting their future expansion remains ...
Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
Open Heart

Periprocedural evaluation of patients with BAV stenosis undergoing TAVR: a machine learning-based study

Background Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for ...
Search Engine Land

New Google TurboQuant algorithm improves vector search speed

Google says a new compression algorithm, called TurboQuant, can compress and search massive AI data sets with near-zero indexing time, potentially removing one of the biggest speed limits in modern ...
Scientific Research Publishing

Samanta, B., Al-Balushi, K.R. and Al-Araimi, S.A. (2003) Artificial Neural Networks and Support Vector Machines with Genetic Algorithm for Bearing Fault Detection. Engineering ...

ABSTRACT: Under variable-speed conditions in modern industry, rolling bearing vibration signals are highly non-stationary, and fault features are easily obscured by speed interference and noise.
Scientific Research Publishing

Efficiency of Classification Algorithms in Monitoring Land Use through Remote Sensing in Sissili Province of Burkina Faso ()

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...
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? Based on our evaluation of all models from both classes ever used in ...
Frontiers

A support vector machine-based tool for rapid pediatric asthma exacerbation risk assessment: development and nursing application

Childhood asthma poses a significant threat to pediatric health, and traditional assessment methods are often inadequate in efficiency and accuracy. This study aims to develop a rapid assessment tool ...
Frontiers

Support vector machine-based classification of bulimia nervosa using diffusion tensor imaging

Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging (DTI) to ...
IEEE

Design of a Generic Fault Diagnosis Model for Electrical Distribution Networks Using a Support Vector Machine (SVM) Algorithm

Abstract: This article presents the design and implementation of a generic model for fault diagnosis in electrical distribution networks, based on the Support Vector Machine (SVM) algorithm. The ...