Comparison of three novelty approaches to constants (Ks) handling in analytic programming powered by SHADE

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63522859" target="_blank" >RIV/70883521:28140/19:63522859 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-97888-8_12" target="_blank" >http://dx.doi.org/10.1007/978-3-319-97888-8_12</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-97888-8_12" target="_blank" >10.1007/978-3-319-97888-8_12</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of three novelty approaches to constants (Ks) handling in analytic programming powered by SHADE

Popis výsledku v původním jazyce

This research deals with the comparison of three novelty approaches for constant estimation in analytic programming (AP) powered by Success-history based Differential evolution (SHADE). AP is a tool for symbolic regression tasks which enables to synthesise an analytical solution based on the required behaviour of the system. This paper offers another strategy to already known and used by the AP from the very beginning and approaches published recently in 2016. This paper compares these procedures and the discussion also includes nonlinear fitting and metaevolutionary approach. As the main evolutionary algorithm, a differential algorithm in the version SHADE for the main process of AP is used. The proposed comparison is performed out on quintic, sextic, Sine 3 and Sine 4 benchmark problems.

Název v anglickém jazyce

Comparison of three novelty approaches to constants (Ks) handling in analytic programming powered by SHADE

Popis výsledku anglicky

This research deals with the comparison of three novelty approaches for constant estimation in analytic programming (AP) powered by Success-history based Differential evolution (SHADE). AP is a tool for symbolic regression tasks which enables to synthesise an analytical solution based on the required behaviour of the system. This paper offers another strategy to already known and used by the AP from the very beginning and approaches published recently in 2016. This paper compares these procedures and the discussion also includes nonlinear fitting and metaevolutionary approach. As the main evolutionary algorithm, a differential algorithm in the version SHADE for the main process of AP is used. The proposed comparison is performed out on quintic, sextic, Sine 3 and Sine 4 benchmark problems.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing, Volume 837

ISBN

978-331997887-1

ISSN

21945357

e-ISSN

—

Počet stran výsledku

12

Strana od-do

134-145

Název nakladatele

Springer Verlag

Místo vydání

Berlín

Místo konání akce

Brno

Datum konání akce

20. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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