Machine learning algorithms for power transformers technical state assessment › Research Explorer

Machine learning algorithms for power transformers technical state assessment

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

DOI

https://doi.org/10.1109/SIBIRCON48586.2019.8958395
Final published version

Alexandra Khalyasmaa
Stanislav A. Eroshenko
Valeriy Tashchilin
Clement Seguin
Lucas Ehlinger
Rohit Rajendra Vibhute
Saikumar Reddy Atluri

Original language	English
Title of host publication	SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	601-606
Number of pages	6
ISBN (Electronic)	9781728144016
DOIs	https://doi.org/10.1109/SIBIRCON48586.2019.8958395
Publication status	Published - Oct 2019
Event	2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 - Novosibirsk, Russian Federation Duration: 21 Oct 2019 → 27 Oct 2019

Publication series

Name	SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings

Conference

Conference	2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
Country/Territory	Russian Federation
City	Novosibirsk
Period	21/10/2019 → 27/10/2019

ASJC Scopus subject areas

Computer Science Applications
Hardware and Architecture
Information Systems and Management
Electrical and Electronic Engineering
Control and Optimization
Instrumentation
Computer Networks and Communications

Research areas

classification, data filtration and recovery, machine learning, power transformer, technical state

ID: 12247396