Evolutionary Identification of Chaotic System

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F09%3A63508019" target="_blank" >RIV/70883521:28140/09:63508019 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Evolutionary Identification of Chaotic System

Popis výsledku v původním jazyce

Abstract: Synthesis, identification and control of complex dynamical systems are usually extremely complicated. When classics methods are used, some simplifications are required which tends to lead to idealized solutions that are far from reality. In contrast, the class of methods based on evolutionary principles is successfully used to solve this kind of problems with a high level of precision. In this paper an alternative method of evolutionary algorithms, which has been successfully proven in many experiments like chaotic systems synthesis, neural network synthesis or electrical circuit synthesis. This paper discusses the possibility of using evolutionary algorithms for the identification of chaotic systems. The main aim of this work is to show thatevolutionary algorithms are capable of the identification of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data. Two different evolutionary algorithms are presented and tested here in a

Název v anglickém jazyce

Evolutionary Identification of Chaotic System

Popis výsledku anglicky

Abstract: Synthesis, identification and control of complex dynamical systems are usually extremely complicated. When classics methods are used, some simplifications are required which tends to lead to idealized solutions that are far from reality. In contrast, the class of methods based on evolutionary principles is successfully used to solve this kind of problems with a high level of precision. In this paper an alternative method of evolutionary algorithms, which has been successfully proven in many experiments like chaotic systems synthesis, neural network synthesis or electrical circuit synthesis. This paper discusses the possibility of using evolutionary algorithms for the identification of chaotic systems. The main aim of this work is to show thatevolutionary algorithms are capable of the identification of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data. Two different evolutionary algorithms are presented and tested here in a

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F09%2F1680" target="_blank" >GA102/09/1680: Evoluční návrh řídicích algoritmů</a><br>

Návaznosti

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

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

2nd IFAC Conference on Analysis and Control of Chaotic Systems

ISBN

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ISSN

1474-6670

e-ISSN

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Počet stran výsledku

8

Strana od-do

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Název nakladatele

International Federation of Automatic Control

Místo vydání

Soul

Místo konání akce

London, UK

Datum konání akce

24. 6. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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