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FUZZY PARTITIONING OF THE OBJECTS BASED ON THE CRITERIA OF DENSITY
2016
Journal:  
Radio Electronics, Computer Science, Control
Author:  
Abstract:

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 Gan G. Data Clustering: theory, algorithms, and applications / G. Gan, C. Ma, J. Wu. – SIAM, Philadelphia, ASA, Alexandria, VA, 2007. – 466 p. 2. Cluster Analysis / [B. Everitt, S. Landau, M. Leese, D. Stahl]. – John Wiley &Sons Ltd, 2011. – 330 p. 3. Xu R. Clustering / R. Xu, D. C. Wunsch. John Wiley &Sons, Inc, 2009. – 358 p. 4. Yager R. Essentials of Fuzzy Modeling and Control / R. Yager, D. Filev. – USA : John Willey & Sons,1984. –387 p. 5. Борисов В. В. Нечеткие модели и сети / В. В. Борисов, В. В. Круглов, А. С. Федулов. – M. : Горячая линия, 2012. – 284 с. 6. Tsoukalas L. H. Fuzzy and Neural Approaches in Engineering / L. H. Tsoukalas, R. E. Uhrig. – New York : John Wiley&Sons.Inc, 1997. – 587 p. 7. Блейхут Р. Теория и практика кодов, контролирующих ошибки / Р. Блейхут. – М. : Мир, 1986. – 576 с. 8. Severance C. Python for Informatics [Electronic resource]. – Regime of access : http://do1.dr-chuck.com/py4inf/EN-us/book.pdf.

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Radio Electronics, Computer Science, Control

Journal Type :   Uluslararası

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Radio Electronics, Computer Science, Control