Generation of Fuzzy Rules by Subtractive ‎ Clustering

Hussen Ateya Lafta; Zahraa A. Mohammed

Article Details

Generation of Fuzzy Rules by Subtractive ‎ Clustering

Authors:

Hussen Ateya Lafta | Zahraa A. Mohammed

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.26 Issue 2, pp.250-259

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001382473

pISSN:

2312-8135

Keywords:

Heart disease diagnoses‎

Abstract:

 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.

Article Details

Generation of Fuzzy Rules by Subtractive ‎ Clustering

Authors: Hussen Ateya Lafta | Zahraa A. Mohammed

Publisher: University of Babylon

Journal: JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.26 Issue 2, pp.250-259

Document Type: Article

Publication Date: 1/2018

Document Language: English

Document ID (Org No.): 2001382473

pISSN: 2312-8135

Heart disease diagnoses‎

Issues

Authors:

Hussen Ateya Lafta | Zahraa A. Mohammed

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.26 Issue 2, pp.250-259

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001382473

pISSN:

2312-8135