Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/75760
Title: Fuzzy neural networks' application for substation integral state assessment
Authors: Khalyasmaa, A. I.
Dmitriev, S. A.
Kokin, S. E.
Eroshenko, S. A.
Issue Date: 2014
Publisher: WITPress
Citation: Fuzzy neural networks' application for substation integral state assessment / A. I. Khalyasmaa, S. A. Dmitriev, S. E. Kokin et al. // WIT Transactions on Ecology and the Environment. — 2014. — Vol. 190 VOLUME 1. — P. 599-605.
Abstract: This paper addresses the problems connected with fuzzy neural networks' application in equipment technical state assessment problems at electrical substations. This paper discusses the main principles of fuzzy neural network formation and its construction algorithm. Also, the case study for the determination of fuzzy neural network synaptic weights for the unit "disconnector" on the basis of technical diagnostic statistical data and tests is presented. © 2014 WIT Press.
Keywords: ELECTRICAL SUBSTATIONS
ENTERPRISE ASSET MANAGEMENT SYSTEMS
FUZZY NEURAL NETWORKS
SYNAPTIC WEIGHTS
TECHNICAL STATE ASSESSMENT
ALGORITHM
ARTIFICIAL NEURAL NETWORK
MANAGEMENT
URI: http://elar.urfu.ru/handle/10995/75760
Access: info:eu-repo/semantics/openAccess
Conference name: 1st International Conference on Energy Production and Management in the 21st Century: The Quest for Sustainable Energy
Conference date: 23 April 2014 through 25 April 2014
SCOPUS ID: 84897894101
PURE ID: 380048
ISSN: 1743-3541
DOI: 10.2495/EQ140581
metadata.dc.description.sponsorship: International Journal of Safety and Security Engineering;International Journal of Sustainable Development and Planning;WIT Transactions on Ecology and the Environment
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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