International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Data Pattern Estimation with Movement of the Center of Gravity

  • Ahn Tae-Chon (Dept. of Control and Instrumentation Engineering, Wonkwang University) ;
  • Jang Kyung-Won (Dept. of Control and Instrumentation Engineering, Wonkwang University) ;
  • Shin Dong-Du (Dept. of Control and Instrumentation Engineering, Wonkwang University) ;
  • Kang Hak-Soo (Dept. of Digital & Electrical Information Engineering, Vision College of Jeonju) ;
  • Yoon Yang-Woong (Dept. of Control and Instrumentation Engineering, Wonkwang University)
  • Published : 2006.09.01
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Abstract

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

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References

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