Health Discovery Corp.

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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 ...
Morning Overview on MSN

Scientists build a ‘periodic table’ for AI models

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...
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 ...
Scientific Research Publishing

Hybrid Software Model for Defect Detection and Cost Evaluation Using Support Vector Machine Algorithm ()

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
IEEE

Artificial Flora Algorithm-Based Feature Selection With Support Vector Machine for Cardiovascular Disease Classification

Abstract: Accurately categorizing medical information is crucial for determining effective cardiac treatment options, especially as the volume of data grows and feature selection becomes increasingly ...