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Fuzzy Logic Systems

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Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSINTELL))

Abstract

In this chapter we present some basic concepts about fuzzy systems needed to better understand the ideas and the concepts of this book.

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References

  1. Sánchez MA, Castillo O, Castro JR (2015) Generalized type-2 fuzzy systems for controlling a mobile robot and a performance comparison with interval type-2 and type-1 fuzzy systems. Expert Syst Appl 42(14):5904–5914

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  3. Sanchez MA, Castro JR, Castillo O (2013, April) Formation of general type-2 Gaussian membership functions based on the information granule numerical evidence. In: 2013 IEEE workshop on hybrid intelligent models and applications (HIMA), pp 1–6. IEEE

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  4. Castillo O, Atanassov K (2019) Comments on fuzzy sets, interval type-2 fuzzy sets, general type-2 fuzzy sets and intuitionistic fuzzy sets. I: Recent advances in intuitionistic fuzzy logic systems, pp 35–43. Springer, Cham

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  5. Mendel JM, Liu F, Zhai D (2009) Alpha-plane representation for type-2 fuzzy sets: theory and applications. IEEE Trans Fuzzy Syst 17(5):1189–1207

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Author information

Authors and Affiliations

  1. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo, Patricia Ochoa & Jose Soria

Authors
  1. Oscar Castillo
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  2. Patricia Ochoa
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  3. Jose Soria
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Corresponding author

Correspondence to Oscar Castillo .

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Castillo, O., Ochoa, P., Soria, J. (2021). Fuzzy Logic Systems. In: Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-030-62133-9_2

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