About: Exotic Metrics for Function Approximation

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Description	In technical practice we are very often confronted with need to approximate functions from measured values. Another frequent task is a calculation of measure of central tendency of sample data. For a good reason the method of least squares and the statistics like mean or median are being used. The goal of this paper is to show some nonstandard metrics usable in tasks of creation of approximation model or in tasks of symbolic regression. These metrics, as will be shown, can be created using so-called generating function. It is important to note these metrics can affect robustness of created model concerning extremely deviated values. Using these exotic metrics in tasks of data approximation or symbolic regression we get nonlinear unconstrained optimization task. To solve such task it is necessary to use adequate optimization strategies such as soft-computing methods (evolution algorithms, HC12, differential evolution, etc.) or classical methods of nonlinear optimization (Nelder-Mead, conjugate gradient In technical practice we are very often confronted with need to approximate functions from measured values. Another frequent task is a calculation of measure of central tendency of sample data. For a good reason the method of least squares and the statistics like mean or median are being used. The goal of this paper is to show some nonstandard metrics usable in tasks of creation of approximation model or in tasks of symbolic regression. These metrics, as will be shown, can be created using so-called generating function. It is important to note these metrics can affect robustness of created model concerning extremely deviated values. Using these exotic metrics in tasks of data approximation or symbolic regression we get nonlinear unconstrained optimization task. To solve such task it is necessary to use adequate optimization strategies such as soft-computing methods (evolution algorithms, HC12, differential evolution, etc.) or classical methods of nonlinear optimization (Nelder-Mead, conjugate gradient (en)
Title	Exotic Metrics for Function Approximation Exotic Metrics for Function Approximation (en)
skos:prefLabel	Exotic Metrics for Function Approximation Exotic Metrics for Function Approximation (en)
skos:notation	RIV/00216305:26210/11:PU96396!RIV12-MSM-26210___
http://linked.open...avai/riv/aktivita	P S Z
http://linked.open...avai/riv/aktivity	P(GA102/09/1680), S, Z(MSM0021630529)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Matoušek, Radomil Karpíšek, Zdeněk
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	Vysoké učení technické v Brně / Fakulta strojního inženýrství
http://linked.open...dnocenehoVysledku	198666
http://linked.open...ai/riv/idVysledku	RIV/00216305:26210/11:PU96396
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	metric, exotic metric, function approximation, generating function (en)
http://linked.open.../riv/klicoveSlovo	metric exotic metric function approximation generating function
http://linked.open...ontrolniKodProRIV	[0BD6EAF41559]
http://linked.open...v/mistoKonaniAkce	Brno University of Technology
http://linked.open...i/riv/mistoVydani	Brno
http://linked.open...i/riv/nazevZdroje	17th International Conference of Soft Computing, MENDEL 2011 (id 19255)
http://linked.open...in/vavai/riv/obor	BB
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Control Algorithm Design by Means of Evolutionary Approach
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Matoušek, Radomil Karpíšek, Zdeněk
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open...ain/vavai/riv/wos	000288144100072
http://linked.open.../riv/zahajeniAkce	2011-06-15 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Inteligentní systémy v automatizaci
number of pages	7 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Vysoké učení technické v Brně
https://schema.org/isbn	978-80-214-4302-0
http://localhost/t...ganizacniJednotka	26210

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