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) ...

Publish your MATLAB® functions to MATLAB Production Server™ as Model Context Protocol (MCP) tools. This allows AI agents to call your functions, enhancing their capabilities with domain-specific ...

Content warning: this story includes discussion of self-harm and suicide. If you are in crisis, please call, text or chat with the Suicide and Crisis Lifeline at 988, or contact the Crisis Text Line ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

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 ...

In seismic structural interpretation, fault detection plays a crucial role as it serves as the foundation and key step for identifying favorable oil and gas zones. Currently, many re-searchers are ...

The adoption of photovoltaic (PV) systems in modern electrical grids has expanded rapidly due to their economic and environmental benefits. However, these systems are prone to faults—such as partial ...