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Generation of Fuzzy Rules by Subtractive Clustering | ||
| Journal of University of Babylon | ||
| Article 1, Volume 26, Issue 2, 2018, Pages 25050-259 | ||
| Authors | ||
| 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. | ||
| Keywords | ||
| Fuzzy rules; First; Subtractive clustering; Heart disease diagnoses; order TSK | ||
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