HUDÍK, Tomáš. The PAH Source Identification Using Positive Matrix Factorization and Clustering Methods. In 6th International Symposium on Environmental Software Systems. Glueph: The International Federation for Information Processing WG 5.11, 2007, p. 63-71. ISBN 978-3-901882-22-7.
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Basic information
Original name The PAH Source Identification Using Positive Matrix Factorization and Clustering Methods
Name in Czech Identifikace PAH zdrojú použitím pozitivní maticové faktorizace a klastrovacích metod
Authors HUDÍK, Tomáš (703 Slovakia, guarantor).
Edition Glueph, 6th International Symposium on Environmental Software Systems, p. 63-71, 2007.
Publisher The International Federation for Information Processing WG 5.11
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Canada
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14330/07:00022439
Organization unit Faculty of Informatics
ISBN 978-3-901882-22-7
Keywords in English machine learning;positive matrix factorization;clustering
Tags clustering, machine learning, positive matrix factorization
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tomáš Hudík, učo 55775. Changed: 7/8/2007 21:22.
Abstract
The goal of this research was to try to find some typical model (representation) according to which climatologists would by able to identify the sources of pollution. We tried some general algorithms like ART2, Xmeans and EM. Although they gave us a lot of results we could not find which of them would be the best. Therefore we tried algorithm called Positive Matrix Factorization which was able to give us some fitness function. With that function we knew how a created model represents the input data.
Abstract (in Czech)
Cílem výzkumu bylo pokusit se najít typický model (reprezentaci) na základě které by klimatologové byli schopni identifikovat zdroje znečištení. Vyzkoušeli jsme několik obecných algoritmů jak ART2, Xmeans a EM. Ačkoli nám daly množství výsledků nebyli jsme schopni zjistit který znich je nejlepší. Proto jsme algoritmus s názvem pozitivní maticová faktorizace, který obsahoval vyhodnocovací funkci. S touhle funkcí jsme vědeli jak vytvořit model reprezentující vstupní data
Links
MSM0021622412, plan (intention)Name: Interakce mezi chemickými látkami, prostředím a biologickými systémy a jejich důsledky na globální, regionální a lokální úrovni (INCHEMBIOL) (Acronym: INCHEMBIOL)
Investor: Ministry of Education, Youth and Sports of the CR, Interactions among the chemicals, environment and biological systems and their consequences on the global, regional and local scales (INCHEMBIOL)
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