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A Dynamic Interval-Valued Intuitionistic Fuzzy Sets Applied to Pattern Recognition

Author

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  • Zhenhua Zhang
  • Min Wang
  • Yong Hu
  • Jingyu Yang
  • Youpei Ye
  • Yafang Li

Abstract

We present dynamic interval-valued intuitionistic fuzzy sets (DIVIFS), which can improve the recognition accuracy when they are applied to pattern recognition. By analyzing the degree of hesitancy, we propose some DIVIFS models from intuitionistic fuzzy sets (IFS) and interval-valued IFS (IVIFS). And then we present a novel ranking condition on the distance of IFS and IVIFS and introduce some distance measures of DIVIFS satisfying the ranking condition. Finally, a pattern recognition example applied to medical diagnosis decision making is given to demonstrate the application of DIVIFS and its distances. The simulation results show that the DIVIFS method is more comprehensive and flexible than the IFS method and the IVIFS method.

Suggested Citation

  • Zhenhua Zhang & Min Wang & Yong Hu & Jingyu Yang & Youpei Ye & Yafang Li, 2013. "A Dynamic Interval-Valued Intuitionistic Fuzzy Sets Applied to Pattern Recognition," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-16, June.
    • Handle: RePEc:hin:jnlmpe:408012
    DOI: 10.1155/2013/408012
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