Outdated targeting data may have resulted in a mistaken missile strike, according to the ongoing military investigation, which undercuts President Trump’s assertion that Iran could be to blame. By ...

Abstract: This paper presents a comprehensive fault classification framework for three-phase Induction Motors (IMs) using a novel Grey Wolf Optimization-enhanced Support Vector Machine (GWO-SVM) ...

Code, configuration templates, and documentation for the PSCC 2026 paper Comparison of Deep Learning Methods for Fault Analysis in Power System Protection. An end-to-end machine learning pipeline for ...

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...

This article was researched using 20 sources. See our methodology and corrections policy. MATLAB is a leading environment for numerical computing, algorithm design, and data analysis used by engineers ...

Speaking at a recent conference panel, officials identified a top use case on their wish list: assisting with the classification of records and the authorization to access those records. “I would ...

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA). A benchmark fault diagnosis dataset comprises ...

IC manufacturers are increasingly relying on intelligent data processing to prevent downtime, improve yields, and reduce scrap. They are integrating that with fault detection and classification (FDC) ...

Reliable fault detection is essential for ensuring the safe and efficient operation of electrochemical energy storage systems, including lithium-ion batteries and transformer. However, the performance ...