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, ...
IEEE

Advanced SVM and KNN Algorithms for Fault Detection in Power Transformers Based on Dissolved Gas Analysis

Abstract: Power transformers, as oil-immersed equipment, are primarily diagnosed using dissolved gas analysis (DGA), a widely recognized and effective fault detection method. Over time, numerous ...
EurekAlert!

Neuromorphic devices and machine learning combine to make brain-like devices possible

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...
Scientific Research Publishing

Keerthi, S.S. (2002) Efficient Tuning of SVM Hyperparameters Using Radius/Margin Bound and Iterative Algorithms. IEEE Transactions on Neural Networks, 13, 1225-1229.

ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...
Frontiers

Integrative single-cell and cell-free plasma RNA transcriptomics identifies biomarkers for early non-invasive AD screening

Data-driven omics approaches have rapidly advanced our understanding of the molecular heterogeneity of Alzheimer’s disease (AD). However, limited by the unavailability of brain tissue, there is an ...
IEEE

Khatri-Rao Factorization Based Bi-Level Support Vector Machine for Hyperspectral Image Classification

Abstract: As a benchmark supervised learning algorithm, support vector machine (SVM) has drawn much attention and reported plenty of impressive results in hyperspectral images (HSIs) classification.