Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine

Review and compare clustering algorithms for navigation data analysis tasks

Authors
Anna Ponomareva, Roman Meyta
Corresponding Author
Anna Ponomareva
Available Online May 2016.
DOI
10.2991/itsmssm-16.2016.58How to use a DOI?
Keywords
Navigation, cluster analysis, GPS, k-means, c-means, DBSCAN, Data Mining.
Abstract

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.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine
Series
Advances in Computer Science Research
Publication Date
May 2016
ISBN
10.2991/itsmssm-16.2016.58
ISSN
2352-538X
DOI
10.2991/itsmssm-16.2016.58How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Anna Ponomareva
AU  - Roman Meyta
PY  - 2016/05
DA  - 2016/05
TI  - Review and compare clustering algorithms for navigation data analysis tasks
BT  - Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine
PB  - Atlantis Press
SP  - 284
EP  - 287
SN  - 2352-538X
UR  - https://doi.org/10.2991/itsmssm-16.2016.58
DO  - 10.2991/itsmssm-16.2016.58
ID  - Ponomareva2016/05
ER  -