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...

Full description

Saved in:
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
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1999-5903/16/12/436

Similar Items