Transformer-based deep learning networks for fault detection, classification, and location prediction in transmission lines-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Transformer-based deep learning networks for fault detection, classification, and location prediction in transmission lines

Published:2024-09-03 Issue: Volume: Page:1-21
ISSN:0954-898X
Container-title:Network: Computation in Neural Systems
language:en
Short-container-title:Network: Computation in Neural Systems

Author:

Baadji Bousaadia¹^ORCID,Belagoune Soufiane²,Boudjellal Sif Eddine³

Affiliation:

1. Institute of Electrical and Electronics Engineering, IGEE, (Ex: Inelec), University of M’hamed Bougara, Boumerdes, Algeria

2. Electrical and Industrial Systems Laboratory (LSEI), Department of Electrical Engineering, Faculty of Electrical Engineering, University of Sciences and Technology of Houari Boumediene (USTHB), Bab Ezzouar, Algeria

3. Laboratoire d’Instrumentation Scientifique (LIS), Electronics Department, University Ferhat Abbas Setif 1, Setif, Algeria

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0954898X.2024.2393746

Reference38 articles.

1. Agarap AF. 2018. Deep learning using rectified linear units (relu). ArXiv Prepr ArXiv180308375.

2. Deep learning through LSTM classification and regression for transmission line fault detection, diagnosis and location in large-scale multi-machine power systems

3. Deep-learning-based data-manipulation attack resilient supervisory backup protection of transmission lines

4. Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

5. A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP