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http://dx.doi.org/10.9708/jksci.2014.19.8.011

Coupled data classification method using unsupervised learning and fuzzy logic in Cloud computing environment  

Cho, Kyu-Cheol (Electronics and Telecommunications Research Institute)
Kim, Jae-Kwon (School of Computer Science and Engineering, Inha University)
Publication Information
Journal of the Korea Society of Computer and Information / v.19, no.8, 2014 , pp. 11-18 More about this Journal
Abstract
In This paper, we propose the unsupervised learning and fuzzy logic-based coupled data classification method base on ART. The unsupervised learning-based data classification helps improve the grouping technique, but decreases the processing efficiency. However, the data classification requires the decision technique to induce high success rate of data classification with optimal threshold. Therefore it is also necessary to solve the uncertainty of the threshold decision. The proposed method deduces the optimal threshold with the designing of fuzzy parameter and rules. In order to evaluate the proposed method, we design the simulation model with the GPCR(G protein coupled receptor) data in cloud computing environment. Simulation results verify the efficiency of our method with the high recognition rate and low processing time.
Keywords
Cloud Computing; Coupled data classification; ART; Fuzzy Logic;
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Times Cited By KSCI : 2  (Citation Analysis)
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