Robust TSK Fuzzy Modeling with Proper Clustering Structure

نویسندگان

  • Chih-Ching Hsiao
  • Shun-Feng Su
چکیده

Traditional approaches for modeling TSK fuzzy rules are trying to adjust the parameters in models, and not considering the training data distribution. Hence it will result in an improper clustering structure, especially, when outliers exist. In this paper, a clustering algorithm termed as Robust Proper Structure Fuzzy Regression Algorithm (RPSFR) is proposed to define fuzzy subspaces in a fuzzy regression manner and also data clustering with robust capability against outliers.

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تاریخ انتشار 2005