Binary Social Impact Theory based Optimization and Its Applications in Pattern Recognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00213845" target="_blank" >RIV/68407700:21230/14:00213845 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S092523121301103X#" target="_blank" >http://www.sciencedirect.com/science/article/pii/S092523121301103X#</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.neucom.2013.03.063" target="_blank" >10.1016/j.neucom.2013.03.063</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Binary Social Impact Theory based Optimization and Its Applications in Pattern Recognition

Popis výsledku v původním jazyce

The human opinion formation can be understood as a social approach to optimization. In the real world, the opinions on different issues encode a ?candidate solution?, which is evaluated by a complex and unknown fitness function. The computer models of such processes can be easily modified by introducing a fitness value, which leads to novel family of optimization techniques. This paper demonstrates how the novel algorithms can be derived from opinion formation models and empirically demonstrates their usability in the area of binary optimization. Particularly, it introduces a general SITO algorithmic framework and describes four algorithms based on this general framework. Recent applications of these algorithms to pattern recognition in electronic nose, electronic tongue, new born EEG and ICU patient mortality prediction are discussed. Finally, an open source SITO library for MATLAB and JAVA is introduced.

Název v anglickém jazyce

Binary Social Impact Theory based Optimization and Its Applications in Pattern Recognition

Popis výsledku anglicky

The human opinion formation can be understood as a social approach to optimization. In the real world, the opinions on different issues encode a ?candidate solution?, which is evaluated by a complex and unknown fitness function. The computer models of such processes can be easily modified by introducing a fitness value, which leads to novel family of optimization techniques. This paper demonstrates how the novel algorithms can be derived from opinion formation models and empirically demonstrates their usability in the area of binary optimization. Particularly, it introduces a general SITO algorithmic framework and describes four algorithms based on this general framework. Recent applications of these algorithms to pattern recognition in electronic nose, electronic tongue, new born EEG and ICU patient mortality prediction are discussed. Finally, an open source SITO library for MATLAB and JAVA is introduced.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

<a href="/cs/project/GP13-21696P" target="_blank" >GP13-21696P: Selekce příznaků pro modely vícedimenzionálních časových řad uvažující časový kontext</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 periodika

Neurocomputing

ISSN

0925-2312

e-ISSN

—

Svazek periodika

132

Číslo periodika v rámci svazku

—

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

85-96

Kód UT WoS článku

000334480500009

EID výsledku v databázi Scopus

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