MIMO Pseudo Neural Networks for Iris Data Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F14%3A43871640" target="_blank" >RIV/70883521:28140/14:43871640 - 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

MIMO Pseudo Neural Networks for Iris Data Classification

Popis výsledku v původním jazyce

This research deals with a novel approach to classification. This paper deals with a synthesis of a complex structure which serves as a classifier. Compared to previous research, this paper synthesizes multi-input-multi-output (MIMO) classifiers. Classical artificial neural networks (ANN) were an inspiration for this work. The proposed technique creates a relation between inputs and outputs as a whole structure together with numerical values which could be observed as weights in ANN. The Analytic Programming (AP) was utilized as the tool of synthesis by means of the evolutionary symbolic regression. Iris data (a known benchmark for classifiers) was used for testing of the proposed method. For experimentation, Differential Evolution for the main procedure and also for meta-evolution version of analytic programming was used.

Název v anglickém jazyce

MIMO Pseudo Neural Networks for Iris Data Classification

Popis výsledku anglicky

This research deals with a novel approach to classification. This paper deals with a synthesis of a complex structure which serves as a classifier. Compared to previous research, this paper synthesizes multi-input-multi-output (MIMO) classifiers. Classical artificial neural networks (ANN) were an inspiration for this work. The proposed technique creates a relation between inputs and outputs as a whole structure together with numerical values which could be observed as weights in ANN. The Analytic Programming (AP) was utilized as the tool of synthesis by means of the evolutionary symbolic regression. Iris data (a known benchmark for classifiers) was used for testing of the proposed method. For experimentation, Differential Evolution for the main procedure and also for meta-evolution version of analytic programming was used.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED2.1.00%2F03.0089" target="_blank" >ED2.1.00/03.0089: Centrum bezpečnostních, informačních a pokročilých technologií (CEBIA-Tech)</a><br>

Návaznosti

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

Rok uplatnění

2014

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. 285

ISBN

978-3-319-06739-1

ISSN

2194-5357

e-ISSN

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Počet stran výsledku

12

Strana od-do

165-172

Název nakladatele

Springer-Verlag Berlin

Místo vydání

Heidelberg

Místo konání akce

online

Datum konání akce

28. 4. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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