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

University of Babylon

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