Abstract: With the advent of modernization, it is inevitable from various sources that there is a significant increase in the energy demand. In order to efficiently meet this demand, we need to ensure ...
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) ...
The New York Court of Appeals in Government Employees Insurance Co. v. Mayzenberg upheld that insurers can deny no-fault claims based on providers’ failure to meet licensing requirements, but not ...
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 ...
A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...
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 = ...
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 ...
ABSTRACT: This paper presents a method for detecting, classifying, and locating short-circuit faults in meshed electrical networks using Artificial Neural Networks (ANNs). The proposed approach is ...
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