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Neural differentiation in modeling

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dc.title Neural differentiation in modeling en
dc.contributor.author Tupý, Jaroslav
dc.contributor.author Oplatková, Zuzana
dc.contributor.author Zelinka, Ivan
dc.relation.ispartof MENDEL 2009
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-80-214-3884-2
dc.date.issued 2009
dc.citation.spage 154
dc.citation.epage 159
dc.event.title 15th International Conference on Soft Computing
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2009-06-24
dc.event.edate 2009-06-26
dc.type conferenceObject
dc.language.iso en
dc.publisher Vysoké učení technické v Brně cs
dc.subject Artificial Neural Network en
dc.subject modeling en
dc.subject approximation en
dc.subject feedforward network en
dc.subject artificial intelligence en
dc.description.abstract The paper deals with a promising approach of modeling the real life systems, characterized with sets Of measured/discrete data, by replacing them with analytical functions framework. The article is focused on neural network approximation of functional expressions. As an analyzed system a dynamic flight model has been chosen due to the necessity of considering several classes of large sets of aerodynamic lift, drag, speed, force, balance and mass data to get a comparable mock-up response. Handling such type of model is naturally a huge computation time demanding process. Being able to substitute it with analytical functions system presenting a coincident behaviour could dramatically improve computation time at all aspects of utilization (UAV/UAS, autopilot systems, flight simulators, real lime control & stability response determination, etc.). Therefore first steps how to obtain analytical function are shown here. In this paper, sample case parameters were used to produce data that were then fitted with an exact function obtained from feedforward neural network en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1001827
utb.identifier.rivid RIV/70883521:28140/09:63508011!RIV10-GA0-28140___
utb.identifier.obdid 43858643
utb.identifier.scopus 2-s2.0-84907929442
utb.identifier.wok 000273029500023
utb.source d-wok
dc.date.accessioned 2011-08-09T07:34:02Z
dc.date.available 2011-08-09T07:34:02Z
utb.contributor.internalauthor Tupý, Jaroslav
utb.contributor.internalauthor Oplatková, Zuzana
utb.contributor.internalauthor Zelinka, Ivan
utb.fulltext.affiliation Jaroslav Tupý, Zuzana Oplatková, Ivan Zelinka Faculty of Applied Informatics, Tomas Bata University, Nad Stráněmi 4511, 720 05 Zlín, Czech Republic | E-mail: {jtupy, oplatková, zelinka}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the grant NO. MSM 7088352101 of the Ministry of Education of the Czech Republic and by grants of Grant Agency of Czech Republic GACR 102/09/1680
utb.fulltext.projects MSM 7088352101
utb.fulltext.projects GACR 102/09/1680
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.ou -
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