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Editor-in-chief
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2016 Vol.8(6): 500-505 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2016.V8.1096

Research on Parameters Optimization of SVM Based on Improved Fruit Fly Optimization Algorithm

Qiantu Zhang, Liqing Fang, Leilei Ma, and Yulong Zhao
Abstract—The performance of the support vector machine (SVM) is determined to a great extent by the parameter selection. In order to improve the learning and generalization ability of SVM, in this paper, an improved fruit fly optimization algorithm (IFOA) was proposed to optimize kernel parameter and penalty factor of SVM. In IFOA, the fruit fly group is dynamically divided into advanced subgroup and drawback subgroup according to its own evolutionary level. A global search is made for the drawback subgroup under the guidance of the best individual and a finely local search is made for the advanced subgroup in which the fruit flies do Levy flight around the best individual. Two subgroups exchange information by updating the overall optimum and recombining the subgroups. Getting rid of local optimum and improve search ability are ensured by making those changes in basic FOA. The performance of the IFOA and classification accuracy of optimized SVM based on IFOA are respectively examined through several typical benchmark functions and classical data sets from UCI benchmark. The experiment results show that the performance of the new algorithm is obviously more successful than FOA and it is also an effective SVM parameter optimization method which has better performance than some other methods.

Index Terms—Support vector machine, fruit fly optimization algorithm, parameter optimization, Levy flight.

Qiantu Zhang, Liqing Fang, and Yulong Zhao are with the First Department, Mechanical Engineering College, PR China (e-mail: qiantuz@sina.com).
Leilei Ma is with the Basic Courses Department, Mechanical Engineering College, PR China.

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Cite:Qiantu Zhang, Liqing Fang, Leilei Ma, and Yulong Zhao, "Research on Parameters Optimization of SVM Based on Improved Fruit Fly Optimization Algorithm," International Journal of Computer Theory and Engineering vol. 8, no. 6, pp. 500-505, 2016.

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