An Ensemble Deep CNN Approach for Power Quality Disturbance Classification: A Technological Route Towards Smart Cities Using Image-Based Transfer

An Ensemble Deep CNN Approach for Power Quality Disturbance Classification: A Technological Route Towards Smart Cities Using Image-Based Transfer

The abundance of powered semiconductor devices has increased with the introduction of renewable energy sources into the grid, causing power quality disturbances (PQDs). This represents a huge challenge for grid reliability and smart city infrastructures. Accurate detection and classification are imp...

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Bibliographic Details
Main Authors:	Mirza Ateeq Ahmed Baig, Naeem Iqbal Ratyal, Adil Amin, Umar Jamil, Sheroze Liaquat, Haris M. Khalid, Muhammad Fahad Zia
Format:	Article
Language:	English
Published:	MDPI AG 2024-11-01
Series:	Future Internet
Subjects:	ensemble learning deep convolution neural networks deep learning machine learning power quality disturbances revolutionary technologies
Online Access:	https://www.mdpi.com/1999-5903/16/12/436
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