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 ...
Frontiers

Retrieving interpretability to support vector machine regression models in dynamic system identification

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...
The New York Times

U.S. Pledges Support for Argentina’s Economy and a Trump Ally in Crisis

Treasury Secretary Scott Bessent said “all options” are under consideration to help President Javier Milei. By Alan Rappeport and Colby Smith Alan Rappeport reported from Washington. Colby Smith ...
IEEE

Support Vector Machine-Integrated High-Definition MCPWM Technique for Improving Power Quality in Multilevel Inverters

Abstract: What if machine learning could predict inverter harmonics before prototyping? Conventional pulse width modulation (PWM) techniques in cascaded H-bridge (CHB) multilevel inverters (MLIs) ...
GitHub

Prediction of stroke using Support Vector Machine (SVM) and Decision Tree (DTREE).

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 ...
Science Daily

Space-laser AI maps forest carbon in minutes—a game-changer for climate science

A pioneering study reveals how archaeologists' satellite tools can be repurposed to tackle climate change. By using AI and satellite LiDAR imagery from NASA and ESA, researchers have found a faster, ...
Scientific Research Publishing

Illa, P.K., Parvathala, B. and Sharma, A.K. (2022) Stock Price Prediction Methodology Using Random Forest Algorithm and Support Vector Machine. Materials Today: Proceedings, 56 ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.