Hybrid Harmony Search and Genetic for Fuzzy Classification Systems
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Authors
Maryam Sadat Mahmoodi
- Department of Computer, Payame Noor University, I.R of IRAN.
Seyed Abbas Mahmoodi
- Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Yazd, Iran.
Abstract
In this paper, a method based on Harmony Search Algorithm (HSA) is proposed for pattern classification. One of the important issues in the design of fuzzy classifier if the product of fuzzy if then rules. So that the number of incorrectly classified patterns is minimized. In the HSA-based method, every musician makes a musical note and it can be regarded as a solution vector. The algorithm uses Genetic algorithm based local search to improve the quality of fuzzy classification system. The proposed algorithm is evaluated on a breast cancer data. The results show that the algorithm based on improved genetic is able to produce a fuzzy classifier to detect breast cancer.
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ISRP Style
Maryam Sadat Mahmoodi, Seyed Abbas Mahmoodi, Hybrid Harmony Search and Genetic for Fuzzy Classification Systems, Journal of Mathematics and Computer Science, 10 (2014), no. 3, 203-211
AMA Style
Mahmoodi Maryam Sadat, Mahmoodi Seyed Abbas, Hybrid Harmony Search and Genetic for Fuzzy Classification Systems. J Math Comput SCI-JM. (2014); 10(3):203-211
Chicago/Turabian Style
Mahmoodi, Maryam Sadat, Mahmoodi, Seyed Abbas. "Hybrid Harmony Search and Genetic for Fuzzy Classification Systems." Journal of Mathematics and Computer Science, 10, no. 3 (2014): 203-211
Keywords
- Harmony Search Algorithm
- Genetic Algorithm
- Fuzzy Classification System.
MSC
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