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http://dx.doi.org/10.5370/KIEE.2010.59.6.1159

Design of HCBKA-Based TSK Fuzzy Prediction System with Error Compensation  

Bang, Young-Keun (강원대 전기전자공학과)
Lee, Chul-Heui (강원대 전기전자공학부)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.59, no.6, 2010 , pp. 1159-1166 More about this Journal
Abstract
To improve prediction quality of a nonlinear prediction system, the system's capability for uncertainty of nonlinear data should be satisfactory. This paper presents a TSK fuzzy prediction system that can consider and deal with the uncertainty of nonlinear data sufficiently. In the design procedures of the proposed system, HCBKA(Hierarchical Correlationship-Based K-means clustering Algorithm) was used to generate the accurate fuzzy rule base that can control output according to input efficiently, and the first-order difference method was applied to reflect various characteristics of the nonlinear data. Also, multiple prediction systems were designed to analyze the prediction tendencies of each difference data generated by the difference method. In addition, to enhance the prediction quality of the proposed system, an error compensation method was proposed and it compensated the prediction error of the systems suitably. Finally, the prediction performance of the proposed system was verified by simulating two typical time series examples.
Keywords
TSK Fuzzy System; HCBKA; Difference Data; Error Compensation; Time Series;
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