Uncertain Fault Diagnosis of Grid-Connected PV Systems based Improved Data-Driven Paradigms-Reference-Cited by-同舟云学术

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Uncertain Fault Diagnosis of Grid-Connected PV Systems based Improved Data-Driven Paradigms

Published:2022-05-06 Issue: Volume: Page:
ISSN:
Container-title:2022 19th International Multi-Conference on Systems, Signals & Devices (SSD)
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Author:

Dhibil Khaled¹,Mansouri Majdi²,Bouzrara Kais¹,Nounou Hazem²,Nounou Mohamed³

Affiliation:

1. National Engineering School of Monastir,Research Laboratory of Automation, Signal Processing and Image,Tunisia,5019

2. Electrical and Computer Engineering Program, Texas A&M, University at Qatar,Doha,Qatar,23874

3. Chemical Engineering Program, Texas A&M University at Qatar,Doha,Qatar,23874

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9955493/9955494/09955664.pdf?arnumber=9955664

Reference23 articles.

1. A comprehensive evaluation of ensemble learning for stock-market prediction

2. Effect of model uncertainty on failure detection: the threshold selector

3. A Hybrid Approach for Process Monitoring: Improving Data-Driven Methodologies With Dataset Size Reduction and Interval-Valued Representation

4. A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation

5. Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches

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