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Abstract
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Article Information:
An Innovative Potential on Rule Optimization using Fuzzy Artificial Bee Colony
K. Sathesh Kumar and M. Hemalatha
Corresponding Author: M. Hemalatha
Submitted: June 11, 2012
Accepted: July 04, 2013
Published: April 05, 2014 |
Abstract:
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This study adapted an improved algorithm based on Artifical Bee Colony Optimization. It is not possible to justify that all the rules generated by fuzzy based apriori algorithm produce optimum result. Thus optimization of the result generated was carried out by Fuzzy Apriori algorithm using Fuzzy Artifical Bee Colony Optimization (FABCO), it's worth noting that a significant findings were revealed. FABCO is used for optimization of rules to get the best classification accuracy. The proposed method was compared with the traditional Artifical bee colony optimization and the particle swarm optimization. The current work proved a better classification performance compared to un-pruned rules.
Key words: Fuzzy ABC algorithm, fuzzy apriori, fuzzy association rule, fuzzy datamining, rule optimization, ,
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Cite this Reference:
K. Sathesh Kumar and M. Hemalatha, . An Innovative Potential on Rule Optimization using Fuzzy Artificial Bee Colony. Research Journal of Applied Sciences, Engineering and Technology, (13): 2627-2633.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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