Review and compare clustering algorithms for navigation data analysis tasks

Bibliographic Details
Parent link:	Advances in Computer Science Research Vol. 51 : Information Technologies in Science, Management, Social Sphere and Medicine (ITSMSSM 2016).— 2016.— [P. 270-273]
Main Author:	Ponomareva A. V. Anna Vladimirovna
Corporate Author:	Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра информатики и проектирования систем (ИПС)
Other Authors:	Meyta R. V. Roman Valerievich
Summary:	Title screen This paper presents a study of the possibility of application of cluster analysis methods to the data sets from navigation receivers. The navigation data from the moving objects have a number of features, it makes the application to them of some class of clustering algorithms impossible. Such features include, in particular, the prevalence of clusters of complex shape different from circle.
Published:	2016
Subjects:	электронный ресурс труды учёных ТПУ navigation cluster analysis GPS k-means c-means DBSCAN data mining навигация кластерный анализ алгоритмы навигационные данные движущие объекты кластеризация
Online Access:	http://dx.doi.org/10.2991/itsmssm-16.2016.58
Format:	Electronic Book Chapter
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=657502

Description
Summary:	Title screen This paper presents a study of the possibility of application of cluster analysis methods to the data sets from navigation receivers. The navigation data from the moving objects have a number of features, it makes the application to them of some class of clustering algorithms impossible. Such features include, in particular, the prevalence of clusters of complex shape different from circle.
DOI:	10.2991/itsmssm-16.2016.58

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