APPLICATION OF HIERARCHICAL CLUSTERING ALGORITHM FOR STRUCTURAL CHARACTERISTIC OF MOVING PHYSICAL OBJECTS

Authors

  • N.I. Babenko Kherson Physics and Mathematics Lyceumof KNTUand DNU, Kherson

DOI:

https://doi.org/10.14308/ite000467

Keywords:

cluster analysis, moving objects, STATISTICA 8

Abstract

     Approach to the development of management solutions using the cluster analysis can qualitatively improve the management system by moving objects through the adequate response to the impact of the key factors influencing the characteristics of physical objects.
     The aim is to attempt to solve the problem of identifying key factors and physical signs of moving physical objects needed to make appropriate management decisions by using cluster analysis.
     The article defines the types of clustering algorithms; the system of information parameters directly or indirectly characterizing the analyzed characteristics is emphasized, hierarchical and non-hierarchical cluster analysis methods are considered.
     The research finding is the construction of tree diagram using the program STATISTICA 8,which gives the idea of possible clusters’ number combining physical indicators under the dynamic changes of moving objects.
     The advantage of cluster analysis usage is the use of factors relating to both internal and external environments of the physical properties’ interaction of moving objects.

Downloads

Metrics

PDF views
Jul 2015Jan 2016Jul 2016Jan 2017Jul 2017Jan 2018Jul 2018Jan 2019Jul 2019Jan 2020Jul 2020Jan 2021Jul 2021Jan 2022Jul 2022Jan 2023Jul 2023Jan 2024Jul 2024Jan 2025Jul 2025Jan 20265.0
|

References

<uk>
1. Мандель И.Д. Кластерный анализ. – М.: Финансы и статистика, 1988. – 176 с.
2. Брюханов В.В. Кластерный анализ как метод определения ключевых факторов. – ГОУ ВПО КГТЭИ, 2006. – С. 33-36.
3. Ким Дж.-О., Мюллер Ч.У. и др. Факторный, дискриминантный и кластерный анализ: Пер. с англ. – М.: Финансы и статистика, 1989. – 215 с.
4. Литвиненко В.И. Кластерный анализ данных на основе модифицированной иммунной сети // УСим. – 2009. – С. 54-61.
5. Ward J.H. Hierarchical grouping to optimize an objective functions // Journal of the American Statistical Association. – 1963. – 236 p.
</uk>
<en>
1. Mandel I.D. Klasternyiy analiz. – M.: Finansyi i statistika, 1988. – 176 s.
2. Bryuhanov V.V. Klasternyiy analiz kak metod opredeleniya klyuchevyih faktorov. – GOU VPO KGTEI, 2006. – S. 33-36.
3. Kim Dzh.-O., Myuller Ch.U. i dr. Faktornyiy, diskriminantnyiy i klasternyiy analiz: Per. s angl. – M.: Finansyi i statistika, 1989. – 215 s.
4. Litvinenko V.I. Klasternyiy analiz dannyih na osnove modifitsirovannoy immunnoy seti // USim. – 2009. – S. 54-61.
5. Ward J.H. Hierarchical grouping to optimize an objective functions // Journal of the American Statistical Association. – 1963. – 236 p.
</en>

Published

05.02.2015

How to Cite

Babenko, N. (2015). APPLICATION OF HIERARCHICAL CLUSTERING ALGORITHM FOR STRUCTURAL CHARACTERISTIC OF MOVING PHYSICAL OBJECTS. Journal of Information Technologies in Education (ITE), (18), 59–64. https://doi.org/10.14308/ite000467