IEEE

Enhancing Power Grid Reliability With Machine Learning and Auxiliary Classifier Generative Adversarial Networks: A Study on Fault Detection Using the Georgia Electric System ...

Abstract: Power networks are vital to society, yet service outages and faults can have devastating consequences. This study introduces a novel integration of machine learning and data augmentation ...
GitHub

IFD for Motor Bearing Fault Detection

This repository contains an Intelligent Fault Detection (IFD) System to detect motor bearing faults in industrial machinery. Uses a 1D-CNN to achieve end-to-end classification from raw vibration ...
IEEE

A Hybrid Approach to Classification Using KNN and MLP Probability Aggregation

Abstract: This research investigates the classification performance of various modeling approaches, including single classifiers, ensemble techniques, and a novel hybrid framework that integrates ...
SciELO

Precision crack analysis in concrete structures using CNN, SVM, and KNN: a machine learning approach

Cracks in structures are discontinuities that occur due to stress, material degradation, or design flaws, compromising structural integrity. Detecting and analyzing cracks is crucial for assessing ...