About: Artificial Neural Networks in Parameter Identification

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Recent decades have witnessed rapid development in numerical modelling of structures as well as materials and the complexity of models increases rapidly together with their computational demands. Despite the growing performance of modern computers and clusters, a suitable approximation of an exhaustive simulation has still many applications in engineering problems. For example, the field of parameters identification may represent a large domain for very efficient applications. The layered neural networks are still considered as very general tools for approximation and they became popular especially for their simple implementation. This contribution presents different strategies for application of neural networks in calibration of affinity hydration model and discusses their possible advantages and drawbacks. Recent decades have witnessed rapid development in numerical modelling of structures as well as materials and the complexity of models increases rapidly together with their computational demands. Despite the growing performance of modern computers and clusters, a suitable approximation of an exhaustive simulation has still many applications in engineering problems. For example, the field of parameters identification may represent a large domain for very efficient applications. The layered neural networks are still considered as very general tools for approximation and they became popular especially for their simple implementation. This contribution presents different strategies for application of neural networks in calibration of affinity hydration model and discusses their possible advantages and drawbacks. (en)
Title	Artificial Neural Networks in Parameter Identification Artificial Neural Networks in Parameter Identification (en)
skos:prefLabel	Artificial Neural Networks in Parameter Identification Artificial Neural Networks in Parameter Identification (en)
skos:notation	RIV/68407700:21110/12:00200025!RIV13-GA0-21110___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GPP105/11/P370)
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Mareš, Tomáš Kučerová, Anna Janouchová, Eliška
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta stavební
http://linked.open...dnocenehoVysledku	123719
http://linked.open...ai/riv/idVysledku	RIV/68407700:21110/12:00200025
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	artificial neural network; multi-layer perceptron; approximation; parameter identification; affinity hydration model; cement paste (en)
http://linked.open.../riv/klicoveSlovo	parameter identification approximation artificial neural network cement paste affinity hydration model multi-layer perceptron
http://linked.open...ontrolniKodProRIV	[C3D7BFC07236]
http://linked.open...v/mistoKonaniAkce	Vídeň
http://linked.open...i/riv/mistoVydani	Vienna
http://linked.open...i/riv/nazevZdroje	Proceedings of the 6th European Congress on Computational Methods in Applied Sciences and Engineering
http://linked.open...in/vavai/riv/obor	JM
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Artificial neural networks in multi-scale modelling of transport processes in heterogeneous materials
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Janouchová, Eliška Kučerová, Anna Mareš, Tomáš
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2012-09-10 (xsd:date)
number of pages	2 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Vienna University of Technology
https://schema.org/isbn	978-3-9502481-9-7
http://localhost/t...ganizacniJednotka	21110

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