An Empirical Evaluation of Transmission Line Fault Identification and Filtration Using Improved Deep Learning Strategy-Reference-Cited by-同舟云学术

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An Empirical Evaluation of Transmission Line Fault Identification and Filtration Using Improved Deep Learning Strategy

Published:2024-04-04 Issue: Volume: Page:1-7
ISSN:
Container-title:2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
language:
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Author:

Nirmala P.¹,Logeswari V.²,Nair M. Saranya³

Affiliation:

1. Saveetha Institute of Medical and Technical Sciences, Saveetha University,Department of ECE, Saveetha School of Engineering,Chennai

2. Nandha Engineering College,Department of ECE,Erode,6380552

3. School of Electronics Engineering (SENSE), Vellore Institute of Technology,Chennai

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10568576/10568577/10568605.pdf?arnumber=10568605

Reference15 articles.

1. Fast and Accurate Fault Detection and Classification in Transmission Lines using Extreme Learning Machine

2. Optimization of Solar Hybrid Power Generation Using Conductance-Fuzzy Dual-Mode Control Method

3. Phasor Domain Single-Ended Transmission Line Fault Location Method Based on Harmonics without Remote Side Information

4. A Novel Approach in Hybrid Energy Storage System for Maximizing Solar PV Energy Penetration in Microgrid

5. Deep-Learning-Based Detection of Transmission Line Insulators

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