Machine Learning in Active Power Filters: Advantages, Limitations, and Future Directions

Machine learning (ML) techniques have permeated various domains, offering intelligent solutions to complex problems. ML has been increasingly explored for applications in active power filters (APFs) due to its potential to enhance harmonic compensation, reference signal generation, filter control op...

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Bibliographic Details
Main Author: Khaled Chahine
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:AI
Subjects:
Online Access:https://www.mdpi.com/2673-2688/5/4/119
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