Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids

Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids

Fault location in DC microgrids (DCMGs) is a critical challenge due to the system’s inherent complexities and the demand for high reliability in modern power systems. This study proposes an explainable artificial intelligence (XAI)-based quantum deep neural network (QDNN) framework to address fault...

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Bibliographic Details
Main Authors: Amir Hossein Poursaeed, Farhad Namdari
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Energies
Subjects:
DC microgrids
fault location
quantum neural networks
explainable artificial intelligence
high-order synchrosqueezing transform
traveling waves
Online Access:https://www.mdpi.com/1996-1073/18/4/908

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https://www.mdpi.com/1996-1073/18/4/908

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