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Generation of fuzzy rules by subtractive clustering
Joint Authors
Muhammad, Zahra Ahmad
Laftah, Husayn Atiyyah
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 26, Issue 2 (28 Feb. 2018), pp.250-259, 10 p.
Publisher
Publication Date
2018-02-28
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
This work depends on two stages.
First one, "subtractive method", clustering algorithm, used for identifying the relationships between data points in order to build system, where the data point gathers with other points to make cluster of the same features.
These groups will be used in the second part of the work to construct fuzzy IF...THEN rules, which controls how the system works.
The number of rules and its parts depend on these clusters.
While the Takagi-Sugeno Kang (TSK) fuzzy inference modal was used.
The scope of this work is applied to heart disease diagnosis.
American Psychological Association (APA)
Laftah, Husayn Atiyyah& Muhammad, Zahra Ahmad. 2018. Generation of fuzzy rules by subtractive clustering. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 26, no. 2, pp.250-259.
https://search.emarefa.net/detail/BIM-1094047
Modern Language Association (MLA)
Laftah, Husayn Atiyyah& Muhammad, Zahra Ahmad. Generation of fuzzy rules by subtractive clustering. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 26, no. 2 (2018), pp.250-259.
https://search.emarefa.net/detail/BIM-1094047
American Medical Association (AMA)
Laftah, Husayn Atiyyah& Muhammad, Zahra Ahmad. Generation of fuzzy rules by subtractive clustering. Journal of Babylon University : Journal of Applied and Pure Sciences. 2018. Vol. 26, no. 2, pp.250-259.
https://search.emarefa.net/detail/BIM-1094047
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 258-259
Record ID
BIM-1094047