Artificial Intelligence Methods in Electrocardiogram and Electroencephalogram Data Clustering

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00155868" target="_blank" >RIV/68407700:21230/09:00155868 - 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

Artificial Intelligence Methods in Electrocardiogram and Electroencephalogram Data Clustering

Popis výsledku v původním jazyce

The paper focuses on the field of artificial intelligence techniques and their use in biomedical data processing. It concerns the clustering techniques inspired by various ant colonies. The behaviour of ant colonies shows many interesting properties thathave been used in static and dynamic combinatorial problem-solving tasks (mostly since 1990). Also applications to data clustering have been proposed. This branch is a subject of ongoing research. After the introduction into the state-of-the-art of ant-colony-inspired metaheuristics, an overview of ant-colony-inspired clustering metaheuristics is presented, together with the ACO_DTree method, developed by the first author, which is based on the autocatalytic collective behaviour of real insect colonies. Over the basic algorithm it involves techniques to increase robustness and performance of the method.

Název v anglickém jazyce

Artificial Intelligence Methods in Electrocardiogram and Electroencephalogram Data Clustering

Popis výsledku anglicky

The paper focuses on the field of artificial intelligence techniques and their use in biomedical data processing. It concerns the clustering techniques inspired by various ant colonies. The behaviour of ant colonies shows many interesting properties thathave been used in static and dynamic combinatorial problem-solving tasks (mostly since 1990). Also applications to data clustering have been proposed. This branch is a subject of ongoing research. After the introduction into the state-of-the-art of ant-colony-inspired metaheuristics, an overview of ant-colony-inspired clustering metaheuristics is presented, together with the ACO_DTree method, developed by the first author, which is based on the autocatalytic collective behaviour of real insect colonies. Over the basic algorithm it involves techniques to increase robustness and performance of the method.

Druh

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

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název periodika

International Journal of Computational Intelligence and Applications

ISSN

1469-0268

e-ISSN

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Svazek periodika

8

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

16

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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