An innovative transformer neural network for fault detection and classification for photovoltaic modules-Reference-Cited by-同舟云学术

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An innovative transformer neural network for fault detection and classification for photovoltaic modules

Published:2024-08 Issue: Volume:314 Page:118718
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Ramadan E.A.,Moawad Nada M.,Abouzalm Belal A.,Sakr Ali A.,Abouzaid Wessam F.^ORCID,El-Banby Ghada M.

Publisher

Elsevier BV

Reference50 articles.

1. A machine learning framework to identify the hotspot in photovoltaic module using infrared thermography;Ali;Sol Energy,2020

2. Automatic fault classification in photovoltaic modules using Convolutional Neural Networks;Alves;Renew Energy,2021

3. A method for hybrid extraction of single-diode model parameters of photovoltaics;Arabshahi;Renew Energy,2020

4. Infrared thermography based defects testing of solar photovoltaic panel with fuzzy rule-based evaluation;Balasubramani;Energies,2020

5. Xception: Deep learning with depthwise separable convolutions;Chollet,2017

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1. A Novel Correlation Feature Self-Assigned Kolmogorov-Arnold Networks for Multi-Energy Load Forecasting in Integrated Energy Systems;2024

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