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Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Druckformat: 1064-2315
ISSN Online: 2163-9337

Volumes:
Volumen 51, 2019 Volumen 50, 2018 Volumen 49, 2017 Volumen 48, 2016 Volumen 47, 2015 Volumen 46, 2014 Volumen 45, 2013 Volumen 44, 2012 Volumen 43, 2011 Volumen 42, 2010 Volumen 41, 2009 Volumen 40, 2008 Volumen 39, 2007 Volumen 38, 2006 Volumen 37, 2005 Volumen 36, 2004 Volumen 35, 2003 Volumen 34, 2002 Volumen 33, 2001 Volumen 32, 2000 Volumen 31, 1999 Volumen 30, 1998 Volumen 29, 1997 Volumen 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v40.i4.30
pages 28-48

Objective Cluster Analysis of Data Based on GMDH

Lyudmila V. Sarycheva
National Mining University, Dnepropetrovsk, Ukraine

ABSTRAKT

We consider the problem of objective cluster analysis of data on the basis of self-organization of clusterization according to GMDH principles. Common approach for classification of selection methods of informative features and search of the best clusterization were suggested. We consider new external criteria of clusterization quality estimation and measures of clusterization similarity. We developed the algorithm for objective cluster analysis of time-spatial data.


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