Improving the accuracy of diagnostic predictions for power transformers by employing a hybrid approach combining SMOTE and DNN-Reference-Cited by-同舟云学术

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Improving the accuracy of diagnostic predictions for power transformers by employing a hybrid approach combining SMOTE and DNN

Published:2024-07 Issue: Volume:117 Page:109232
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Gamel Samah A.^ORCID,Ghoneim Sherif S.M.,Sultan Yara A.^ORCID

Publisher

Elsevier BV

Reference30 articles.

1. Winds of Power: data Analysis for the relationship between wind speed, gust, and power output;Gamel;J Eng Res (Ponta Grossa),2023

2. Enhancing the diagnostic accuracy of DGA techniques based on IEC-TC10 and related databases;Gouda;IEEE ACCESS,2021

3. Improvement of power transformer fault diagnosis by using sequential Kalman filter sensor fusion;Demirci;Int J Electr Pow Energy Syst,2023

4. Application of a general regression neural network for health index calculation of power transformers;Islam;Int J Electr Pow Energy Syst,2017

5. Diagnosis and prognosis of incipient faults and insulation status for asset management of power transformer using fuzzy logic controller & fuzzy clustering means;Soni;Electr Pow Syst Res,2023

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