DocumentCode
2592062
Title
Constructing Markov Models for Reliability Assessment with Self-Organizing Maps
Author
Sperandio, Mauricio ; Coelho, Jorge
Author_Institution
Univ. Fed. de Santa Catarina, Florianopolis
fYear
2006
fDate
11-15 June 2006
Firstpage
1
Lastpage
5
Abstract
This paper shows how a pattern recognition method, the self-organizing maps (SOM) or the Kohonen´s neural network, can be used to construct a Markov model by means of state assignment to a process. This turns possible an easy and fast reliability study of power systems
Keywords
Markov processes; power system analysis computing; power system reliability; self-organising feature maps; state assignment; Kohonen´s neural network; Markov model; SOM; pattern recognition method; power systems; reliability study; self-organizing feature map; state assignment; Markov processes; Mathematical model; Monitoring; Neural networks; Pattern recognition; Power system analysis computing; Power system modeling; Power system reliability; Self organizing feature maps; Voltage; Markov processes; Reliability modeling; Self-organizing feature maps; State assignment;
fLanguage
English
Publisher
ieee
Conference_Titel
Probabilistic Methods Applied to Power Systems, 2006. PMAPS 2006. International Conference on
Conference_Location
Stockholm
Print_ISBN
978-91-7178-585-5
Type
conf
DOI
10.1109/PMAPS.2006.360309
Filename
4202321
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