Artificial Intelligence Methods in Electrocardiogram and Electroencephalogram Data Clustering

Result code in 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>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Artificial Intelligence Methods in Electrocardiogram and Electroencephalogram Data Clustering

Original language description

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.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

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

Name of the periodical

International Journal of Computational Intelligence and Applications

ISSN

1469-0268

e-ISSN

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Volume of the periodical

8

Issue of the periodical within the volume

1

Country of publishing house

SG - SINGAPORE

Number of pages

16

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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