The core idea of LCQHNN is to center on quantum feature amplification (Quantum Feature Amplification) while combining a classical stability optimization strategy, establishing an efficient information ...
Abstract: Over the years, researchers have proposed numerous Twin Support Vector Machines (TSVM) variants aimed at addressing diverse challenges. These variants encompass sparse TSVM models, robust ...
The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...
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 ...
Abstract: Classification tasks have long been a central concern in the field of machine learning. Although deep neural network-based approaches offer a novel, versatile, and highly precise solution ...
ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...
1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
This project explores the mathematical and practical implementation of Support Vector Machines (SVMs) optimized using Stochastic Gradient Descent (SGD). It includes a theoretical foundation, algorithm ...