Generation of Fuzzy Rules by Subtractive ‎ Clustering

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Hussen Ateya Lafta
Zahraa A. Mohammed

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.

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How to Cite
[1]
“Generation of Fuzzy Rules by Subtractive ‎ Clustering”, JUBPAS, vol. 26, no. 2, pp. 250–259, Dec. 2017, Accessed: Apr. 21, 2025. [Online]. Available: https://journalofbabylon.com/index.php/JUBPAS/article/view/537
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Articles

How to Cite

[1]
“Generation of Fuzzy Rules by Subtractive ‎ Clustering”, JUBPAS, vol. 26, no. 2, pp. 250–259, Dec. 2017, Accessed: Apr. 21, 2025. [Online]. Available: https://journalofbabylon.com/index.php/JUBPAS/article/view/537

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