This HTML5 document contains 45 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dctermshttp://purl.org/dc/terms/
n18http://purl.org/net/nknouf/ns/bibtex#
n9http://localhost/temp/predkladatel/
n13http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n6http://linked.opendata.cz/ontology/domain/vavai/
n11https://schema.org/
n5http://linked.opendata.cz/resource/domain/vavai/zamer/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n4http://linked.opendata.cz/ontology/domain/vavai/riv/
n15http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F70883521%3A28110%2F07%3A63505132%21RIV08-MSM-28110___/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n10http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n20http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n16http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n7http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n19http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n17http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n8http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F70883521%3A28110%2F07%3A63505132%21RIV08-MSM-28110___
rdf:type
n6:Vysledek skos:Concept
dcterms:description
The laser micro-machining is process which has several input parameters. These input parameters have to be set very carefully in order to obtain desired product. Main product quality characteristics are surface quality and depth of the groove. The examined input parameters of used laser machine were two - power of laser beam and feed. Influences of this two input parameters are contradictory. The higher the power is, the deeper the groove is and higher surface roughness is obtained. Nevertheless, the higher the feed is, the shallower the groove is and the lower surface roughness is. It is difficult to find good combination of these two parameters for desired output product quality. Moreover, dependence between single input parameter and single output characteristic is nonlinear what makes modelling by classical approaches even more complicated. In this paper artificial multilayer feed-forward neural network is used for modelling of behaviour between input and output parameters of laser micro-machining Laserové mikroobrábění je proces, který má několik vstupních parametrů. Pro dosažení produktu s požadovanými vlastnostmi musí být tyto parametry nastavovány velmi opatrně. V tomto článku je použita umělá neuronová vícevrstvá síť s dopředním šířením pro modelování složitých závislostí mezi vstupními parametry mikroobráběcího stroje a výstupními parametry obrobku. Úkolem umělé neuronové sítě je navrhovat nejvhodnější kombinaci vstupních parametrů stroje pro požadované výstupní charakteristiky výrobku. Tento prediktivní model laserového mikroobrábění je experimentálně verifikován The laser micro-machining is process which has several input parameters. These input parameters have to be set very carefully in order to obtain desired product. Main product quality characteristics are surface quality and depth of the groove. The examined input parameters of used laser machine were two - power of laser beam and feed. Influences of this two input parameters are contradictory. The higher the power is, the deeper the groove is and higher surface roughness is obtained. Nevertheless, the higher the feed is, the shallower the groove is and the lower surface roughness is. It is difficult to find good combination of these two parameters for desired output product quality. Moreover, dependence between single input parameter and single output characteristic is nonlinear what makes modelling by classical approaches even more complicated. In this paper artificial multilayer feed-forward neural network is used for modelling of behaviour between input and output parameters of laser micro-machining
dcterms:title
Verification of the predictor of laser micro-machining input parametrs Verification of the predictor of laser micro-machining input parametrs Verifikace prediktoru vstupních parametrů laserového mikroobrábění
skos:prefLabel
Verifikace prediktoru vstupních parametrů laserového mikroobrábění Verification of the predictor of laser micro-machining input parametrs Verification of the predictor of laser micro-machining input parametrs
skos:notation
RIV/70883521:28110/07:63505132!RIV08-MSM-28110___
n4:strany
149-154
n4:aktivita
n7:Z
n4:aktivity
Z(MSM7088352102)
n4:dodaniDat
n8:2008
n4:domaciTvurceVysledku
n13:6639801 n13:3590755
n4:druhVysledku
n17:D
n4:duvernostUdaju
n20:S
n4:entitaPredkladatele
n15:predkladatel
n4:idSjednocenehoVysledku
457794
n4:idVysledku
RIV/70883521:28110/07:63505132
n4:jazykVysledku
n16:eng
n4:klicovaSlova
laser; micro-machining; prediction; surface quality; artificial neural network; multilayer feed-forward neural network
n4:klicoveSlovo
n10:micro-machining n10:prediction n10:laser n10:surface%20quality n10:artificial%20neural%20network n10:multilayer%20feed-forward%20neural%20network
n4:kontrolniKodProRIV
[A661CF001F34]
n4:mistoVydani
Miskolc
n4:nazevZdroje
microCAD 2007
n4:obor
n19:JJ
n4:pocetDomacichTvurcuVysledku
2
n4:pocetTvurcuVysledku
2
n4:rokUplatneniVysledku
n8:2007
n4:tvurceVysledku
Sýkorová, Libuše Sámek, David
n4:zamer
n5:MSM7088352102
s:numberOfPages
6
n18:hasPublisher
University of Miskolc
n11:isbn
978-963-661-753-0
n9:organizacniJednotka
28110