TBU Publications
Repository of TBU Publications

Prediction of technological parameters during polymer material grinding

DSpace Repository

Show simple item record


dc.title Prediction of technological parameters during polymer material grinding en
dc.contributor.author Sámek, David
dc.contributor.author Bílek, Ondřej
dc.contributor.author Černý, Jakub
dc.relation.ispartof Recent Researches in Automatic Control - 13th WSEAS International Conference on Automatic Control, Modelling and Simulation, ACMOS'11
dc.identifier.isbn 9781618040046
dc.date.issued 2011
dc.citation.spage 148
dc.citation.epage 151
dc.event.title 13th WSEAS International Conference on Automatic Control, Modelling and Simulation, ACMOS'11
dc.event.location Lanzarote, Canary Islands
utb.event.state-en Spain
utb.event.state-cs Španělsko
dc.event.sdate 2011-05-27
dc.event.edate 2011-05-29
dc.type conferenceObject
dc.language.iso en
dc.relation.uri http://www.wseas.us/e-library/conferences/2011/Lanzarote/ACMOS/ACMOS-26.pdf
dc.subject Artificial neural networks en
dc.subject Grinding en
dc.subject Prediction en
dc.subject Radial basis function en
dc.description.abstract This article introduces an application of artificial neural network with radial basis function in modeling of polymer materials grinding. This real technological process has many input parameters that influence results of grinding. In this paper the two key parameters were selected - feed rate and depth of cut. The task of the artificial neural network based predictor is to provide resulting surface roughness (Ra and Rz). en
utb.faculty Faculty of Technology
dc.identifier.uri http://hdl.handle.net/10563/1004814
utb.identifier.obdid 43866835
utb.identifier.scopus 2-s2.0-82555178565
utb.source d-scopus
dc.date.accessioned 2015-06-04T12:55:35Z
dc.date.available 2015-06-04T12:55:35Z
utb.contributor.internalauthor Sámek, David
utb.contributor.internalauthor Bílek, Ondřej
utb.contributor.internalauthor Černý, Jakub
Find Full text

Files in this item

Show simple item record