About: OPTIMIZATION OF MODELS: LOOKING FOR THE BEST STRATEGY

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: OPTIMIZATION OF MODELS: LOOKING FOR THE BEST STRATEGY Goto Sponge NotDistinct Permalink

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

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	When parameters of model are being adjusted, model is learning to mimic the behaviour of a real world system. Optimization methods are responsible for parameters adjustment. The problem is that each real world system is different and its model should be of different complexity. It is almost impossible to decide which optimization method will perform the best (optimally adjust parameters of the model). In this paper we compare the performance of several methods for nonlinear parameters optimization. The gradient based methods such as Quasi-Newton or Conjugate Gradient are compared to several nature inspired methods. We designed an evolutionary algorithm selecting the best optimization methods for models of various complexity. Our experiments proved that the evolution of optimization methods for particular problems is very promising approach. When parameters of model are being adjusted, model is learning to mimic the behaviour of a real world system. Optimization methods are responsible for parameters adjustment. The problem is that each real world system is different and its model should be of different complexity. It is almost impossible to decide which optimization method will perform the best (optimally adjust parameters of the model). In this paper we compare the performance of several methods for nonlinear parameters optimization. The gradient based methods such as Quasi-Newton or Conjugate Gradient are compared to several nature inspired methods. We designed an evolutionary algorithm selecting the best optimization methods for models of various complexity. Our experiments proved that the evolution of optimization methods for particular problems is very promising approach. (en) V tomto článku porovnáváme výsledky mnoha metod (gradientních, genetika, hejna) pro optimalizaci spojitých parametrů modelu. Navrhli jsme evoluční algoritmus, který vhodné optimalizační metody vybere automaticky na základě charakteru dat. První výsledky naznačují, že se jedná o velmi slibný přístup. (cs)
Title	OPTIMIZATION OF MODELS: LOOKING FOR THE BEST STRATEGY Optimalizace modelů: hledání nejlepší strategie (cs) OPTIMIZATION OF MODELS: LOOKING FOR THE BEST STRATEGY (en)
skos:prefLabel	OPTIMIZATION OF MODELS: LOOKING FOR THE BEST STRATEGY Optimalizace modelů: hledání nejlepší strategie (cs) OPTIMIZATION OF MODELS: LOOKING FOR THE BEST STRATEGY (en)
skos:notation	RIV/68407700:21230/07:03133126!RIV08-AV0-21230___
http://linked.open.../vavai/riv/strany	314;320
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(KJB201210701), Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat	2008
http://linked.open...aciTvurceVysledku	Kovářík, Oleg Kordík, Pavel Šnorek, Miroslav
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 elektrotechnická
http://linked.open...dnocenehoVysledku	439884
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/07:03133126
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	ACO; Conjugate Gradient Method; Differential Evolution; GAME; Genetic Algorithms; PSO; Quasi Newton method; optimization (en)
http://linked.open.../riv/klicoveSlovo	ACO Genetic Algorithms optimization GAME Differential Evolution PSO Conjugate Gradient Method Quasi Newton method
http://linked.open...ontrolniKodProRIV	[0B3ABE0E2ADE]
http://linked.open...v/mistoKonaniAkce	Ljubljana
http://linked.open...i/riv/mistoVydani	Vienna
http://linked.open...i/riv/nazevZdroje	Proceedings of the 6th EUROSIM Congress on Modelling and Simulation
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Automated Knowledge Extraction
http://linked.open...UplatneniVysledku	2007
http://linked.open...iv/tvurceVysledku	Kordík, Pavel Kovářík, Oleg Šnorek, Miroslav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2007-09-09 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Transdisciplinární výzkum v oblasti biomedicínského inženýrství II
number of pages	7 (xsd:int)
http://purl.org/ne...btex#hasPublisher	ARGESIM
https://schema.org/isbn	978-3-901608-32-2
http://localhost/t...ganizacniJednotka	21230

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 77 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software