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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Печать: 1064-2315
ISSN Онлайн: 2163-9337

Выпуски:
Том 52, 2020 Том 51, 2019 Том 50, 2018 Том 49, 2017 Том 48, 2016 Том 47, 2015 Том 46, 2014 Том 45, 2013 Том 44, 2012 Том 43, 2011 Том 42, 2010 Том 41, 2009 Том 40, 2008 Том 39, 2007 Том 38, 2006 Том 37, 2005 Том 36, 2004 Том 35, 2003 Том 34, 2002 Том 33, 2001 Том 32, 2000 Том 31, 1999 Том 30, 1998 Том 29, 1997 Том 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v47.i10.50
pages 45-59

Matching of External Criterion and Method of Sample Partitioning for Solving Problem of Structural-Parametric Identification by Group Method of Data Handling

Nina V. Kondrashova
International Research and Training Center of Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

Краткое описание

We investigated the validity of the joint application of the data partitioning method and criterion of external additions in finding the most accurate models. Quasi-optimal partitions for all ratios of sizes of the initial matrices are described. GMDH external criteria are comprehensively investigated. Their use in certain types of optimal ways of partitioning the sample is theoretically justified. If the condition of proportionality of data is satisfied, it was theoretically substantiated and confirmed in numerical experiments that the criterion of parameters unbiasedness is not "adequate" to noise while minimizing the criterion of the sample division, it takes place only when it is maximized.


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