Learning patterns from data by an evolutionary-fuzzy approach

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86080817" target="_blank" >RIV/61989100:27240/11:86080817 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-642-19644-7_14" target="_blank" >http://dx.doi.org/10.1007/978-3-642-19644-7_14</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-19644-7_14" target="_blank" >10.1007/978-3-642-19644-7_14</a>

Result language

angličtina

Original language name

Learning patterns from data by an evolutionary-fuzzy approach

Original language description

There are various techniques for data mining and data analysis. Among them, hybrid approaches combining two or more algorithms gain importance as the complexity and dimension of real world data sets grows. In this paper, we present an application of evolutionary-fuzzy classification technique to data mining. Genetic programming is deployed to evolve a fuzzy classifier describing a set of anomalous patterns in data and the classifier is further used to prevent production of faulty products.

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

IN - Informatics

OECD FORD branch

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Project

<a href="/en/project/GA102%2F09%2F1494" target="_blank" >GA102/09/1494: New methods od data transmition based on turbo code</a><br>

Continuities

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

Publication year

2011

Confidentiality

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

Name of the periodical

Advances in Soft Computing

ISSN

1615-3871

e-ISSN

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Volume of the periodical

87

Issue of the periodical within the volume

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Country of publishing house

DE - GERMANY

Number of pages

8

Pages from-to

127-135

UT code for WoS article

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EID of the result in the Scopus database

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