Temperature Distributions Comparison by the Clustering of Their Proximity Measure; Control and Communications (SIBCON)

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Parent link:	Control and Communications (SIBCON).— 2016.— [5 p.]
Korporativní autor:	Томский политехнический университет Институт кибернетики, ИК
Další autoři:	Nemirovskiy V. B. Viktor Borisovich, Stoyanov A. K. Aleksandr Kirillovich, Gofman A. K. Aleksandr Konstantinovich, Tartakovsky V. A. Valery Abramovich
Shrnutí:	Title screen In this paper the method for determining ofproximity of the temperature measurements fields is described.The method includes a clustering of values of the measurementsfields, an estimationof their informational proximity to thechosen reference field by Kullback-Leibler distances and aclustering of thevalues of these distances.Clustering is performedby recurrent neural network. The results of applying theproposed method to the analysis of temperature fields in theNorthern hemisphere for the period of 1955-2010 are presented.
Jazyk:	angličtina
Vydáno:	2016
Edice:	Computer Measurement Technologies
Témata:	электронный ресурс труды учёных ТПУ кластеризация одномерные отображения нейронные сети поля измерения температура
On-line přístup:	http://dx.doi.org/10.1109/SIBCON.2016.7491730
Médium:	Elektronický zdroj Kapitola
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=648812

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