Neuronová sít jako klasifikátor a predikátor zbytkové životnosti VN izolačních materiálů.

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F04%3APU48331" target="_blank" >RIV/00216305:26210/04:PU48331 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Neural Network with Radial Basis Functions as Residual Lifetime Predictor and Classifier of High Voltage Insulating Materials.

Popis výsledku v původním jazyce

This contribution deals with the RBF neural network with radial basis transfer function improvement for residual lifetime prediction and classification of the Relanex insulating material which is used for electric rotary machine winding. This neural network is used for prediction of the residual lifetime of insulating material for the future on the basis of measured values which were measured on the electric machine in previous times. The output from neural network in this case is always a numeric valuee of magnitude characterizing the state of residual lifetime. The RBF neural network can be used as a classifier, too, where, on the basis of measured input data, the neural network verbally determines the residual lifetime for example and that means that the neural network classifies its state. The classification by neural network means to determine the residual lifetime and to classify those values into the predetermined number of categories which characterize the total state of the in

Název v anglickém jazyce

Neural Network with Radial Basis Functions as Residual Lifetime Predictor and Classifier of High Voltage Insulating Materials.

Popis výsledku anglicky

This contribution deals with the RBF neural network with radial basis transfer function improvement for residual lifetime prediction and classification of the Relanex insulating material which is used for electric rotary machine winding. This neural network is used for prediction of the residual lifetime of insulating material for the future on the basis of measured values which were measured on the electric machine in previous times. The output from neural network in this case is always a numeric valuee of magnitude characterizing the state of residual lifetime. The RBF neural network can be used as a classifier, too, where, on the basis of measured input data, the neural network verbally determines the residual lifetime for example and that means that the neural network classifies its state. The classification by neural network means to determine the residual lifetime and to classify those values into the predetermined number of categories which characterize the total state of the in

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F03%2F0621" target="_blank" >GA102/03/0621: Ireverzibilní procesy v elektroizolačních materiálech pro vysoké teploty</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2004

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

3rd International Conference, ICPE-CA 2004

ISBN

973-718-026-7

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

140-144

Název nakladatele

Petrosani (Romania)

Místo vydání

Petrosani

Místo konání akce

Bucharest

Datum konání akce

1. 7. 2004

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

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