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Method for Uncertainty Measurement and Its Application to the Formation of Interval Type-2 Fuzzy Sets

  • Mauricio A. SanchezEmail author
  • Oscar Castillo
  • Juan R. Castro
Conference paper
  • 424 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 401)

Abstract

This paper proposes a new method for directly discovering the uncertainty from a sample of discrete data, which is then used in the formation of an Interval Type-2 Fuzzy Inference System. A Coefficient of Variation is used to measure the uncertainty on a finite sample of discrete data. Based on the maximum possible coverage area of the Footprint of Uncertainty of Gaussian membership functions, with uncertainty on the standard deviation, which then are modified according to the found index values, obtaining all antecedents in the process. Afterwards, the Cuckoo Search algorithm is used to optimize the Interval Sugeno consequents of the Fuzzy Inference System. Some sample datasets are used to measure the output interval coverage.

Keywords

Membership Function Data Pair Reference Target Gaussian Membership Function Output Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

We thank the MyDCI program of the Division of Graduate Studies and Research, UABC, and Tijuana Institute of Technology the financial support provided by our sponsor CONACYT contract grant number: 314258.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mauricio A. Sanchez
    • 1
    Email author
  • Oscar Castillo
    • 2
  • Juan R. Castro
    • 1
  1. 1.Autonomous University of Baja CaliforniaTijuanaMexico
  2. 2.Tijuana Institute of TechnologyTijuanaMexico

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