Improved artificial bee colony algorithm and its application in classification

Authors: Wang, H., Wei, J., Wen, S., Yu, H. and Zhang, X.

Journal: Journal of Robotics and Mechatronics

Volume: 30

Issue: 6

Pages: 921-926

Publisher: Fuji

ISSN: 1883-8049

Haiquan Wang*, Jianhua Wei**, Shengjun Wen*, Hongnian Yu***, and Xiguang Zhang

This data was imported from Scopus:

Authors: Wang, H., Wei, J., Wen, S., Yu, H. and Zhang, X.

Journal: Journal of Robotics and Mechatronics

Volume: 30

Issue: 6

Pages: 921-926

eISSN: 1883-8049

ISSN: 0915-3942

DOI: 10.20965/jrm.2018.p0921

© 2018, Fuji Technology Press. All rights reserved. For improving the classification accuracy of the classifier, a novel classification methodology based on artificial bee colony algorithm is proposed for optimal feature and SVM parameters selection. In order to balance the ability of exploration and exploitation of traditional ABC algorithm, improvements are introduced for the generation of initial solution set and onlooker bee stage. The proposed algorithm is applied to four datasets with different attribute characteristics from UCI and efficiency of the algorithm is proved from the results.

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