Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

Tan, Chin Hooi and Tan, Mei Sze and Chang, Siow Wee and Yap, Keem Siah and Yap, Hwa Jen and Wong, Shen Yuong (2018) Genetic algorithm fuzzy logic for medical knowledge-based pattern classification. Journal of Engineering Science and Technology, 13. pp. 242-258. ISSN 1823-4690,

Full text not available from this repository.
Official URL:


Hybrid of genetic algorithm and fuzzy logic in genetic fuzzy system exemplifies the advantage of best heuristic search with ease of understanding and interpretability. This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. GAFL, with simplistic binary coding scheme using Pittsburg approach managed to exploit the potential of genetic fuzzy inference system with ease of comprehension in fuzzy rules induction in knowledge pattern recognition. The proposed algorithm was tested with three public available medical datasets, which are Wisconsin Breast Cancer (WBC) dataset, Pima Indian Diabetes dataset (PID), Parkinson Disease dataset (PD) and one locally collected oral cancer dataset. The results obtained showed that GAFL outperformed most of the other models that acknowledged from the previous studies. GAFL possessed the advantage of fuzzy rules extraction feature apart from conventional classification technique compared to other models which are lack of fuzzy interpretation. It is easier to interpret and understand fuzzy value in contrast to continuous or range value. GAFL outperformed the other algorithms in terms of accuracy without compromising on interpretability. It is vital to obtain high accuracy in medical pattern recognition especially when dealing with critical illness.

Item Type: Article
Funders: University of Malaya, UMRG Programme with grant number RP038A-15AET, RP038C-15AET, Universiti Tenaga Nasional with grant number J510050684, Tenaga Nasional Berhad
Uncontrolled Keywords: Computational intelligence; Fuzzy logic; Genetic algorithm; Genetic fuzzy system; Knowledge discovery; Pattern classification; Rules induction; Rules learning
Subjects: Q Science > Q Science (General)
Q Science > QH Natural history
T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering
Faculty of Science > Institute of Biological Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 04 Mar 2019 02:09
Last Modified: 04 Mar 2019 02:09

Actions (login required)

View Item View Item