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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications pp 63–71Cite as

Optimization for Type-1 and Interval Type-2 Fuzzy Systems for the Classification of Blood Pressure Load Using Genetic Algorithms

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 862))

Abstract

In this paper, the design of type-1 and interval type-2 fuzzy systems using genetic algorithm is defined. Fuzzy systems are built from the experience of an expert, in this case a cardiologist. The main contribution of this work is to provide the optimization structure for the classification of the blood pressure load in a patient. The decision was made to use genetic algorithms for the optimization of membership functions, which help to improve the classification and provide a better diagnosis to the patient. In addition, the fuzzy systems have fuzzy rules, which are designed from the categories already defined by an expert. After performing some experiments with different type-1 and type-2 fuzzy systems for the classification of blood pressure load, it was concluded that it is necessary to optimize the membership functions to have better results.

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Acknowledgements

We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, BC, Mexico

    Juan Carlos Guzmán & Patricia Melin

  2. Excel Medical Center, Tijuana, Mexico

    German Prado-Arechiga

Authors
  1. Juan Carlos Guzmán
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  2. Patricia Melin
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  3. German Prado-Arechiga
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Corresponding author

Correspondence to Patricia Melin .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Guzmán, J.C., Melin, P., Prado-Arechiga, G. (2020). Optimization for Type-1 and Interval Type-2 Fuzzy Systems for the Classification of Blood Pressure Load Using Genetic Algorithms. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 862. Springer, Cham. https://doi.org/10.1007/978-3-030-35445-9_5

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