FUZZY PARTITIONING OF THE OBJECTS BASED ON THE CRITERIA OF DENSITY

Authors

  • Ye. I. Kucherenko Kharkiv National University of Radio Electronics, Kharkiv, Ukraine
  • I. S. Glushenkova O. M. Beketov National University of Urban Ekonomy in Kharkiv, Kharkov, Ukraine
  • S. A. Glushenkov O. M. Beketov National University of Urban Ekonomy in Kharkiv, Kharkov, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2016-1-4

Keywords:

Clustering, Hamming distance, mountain clustering, fuzzy logic.

Abstract

The problem of the partition of the criteria in the fuzzy space density of states at the intersection of features. The object of research is the process of partitioning a given sample of objects into subsets. Subject of research methods and algorithms make fuzzy partition of objects based on the criteria density in complex systems. Objective: to develop a method of clustering mining Jager-Fileva based on fuzzy concepts to improve the effectiveness of the decisions. It was proposed fuzzy partitioning method based on the calculation of the density distribution of the integral attributes of the objects in a fuzzy space of conditions. The method, in contrast to existing, additionally operates in a fuzzy state space and features. Describe and justify the steps of the method of fuzzy partitioning features using fuzzy Hamming distance. It was created simulation program distribution density of features on the basis of this method. An experiments conducted to determine the affiliation of the object at the intersection of fuzzy areas of distribution and the provision of evidence of results in the form of inference and graphic material. The experimental results allow us to recommend the proposed method to be used in practice. Prospects for further research is to study and algorithmization method, its adaptation to the feature space domains.

References

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Published

2015-10-28

How to Cite

Kucherenko, Y. I., Glushenkova, I. S., & Glushenkov, S. A. (2015). FUZZY PARTITIONING OF THE OBJECTS BASED ON THE CRITERIA OF DENSITY. Radio Electronics, Computer Science, Control, (1). https://doi.org/10.15588/1607-3274-2016-1-4

Issue

Section

Neuroinformatics and intelligent systems