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Ensemble Neural Network Optimization Using a Gravitational Search Algorithm with Interval Type-1 and Type-2 Fuzzy Parameter Adaptation in Pattern Recognition Applications

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Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 749))

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Abstract

In this paper we consider the problem of optimizing ensemble neural networks for pattern recognition with Type-1 and Type-2 fuzzy logic for parameter adaptation in the gravitational search algorithm. The database to be used is of echocardiography images, since these images are very important in clinical echocardiography, and these images help the doctors to diagnose cardiac diseases, as well as to prevent this type of diseases in patient treatment.

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Author information

Authors and Affiliations

  1. Tijuana Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico

    Beatriz González, Patricia Melin & Fevrier Valdez

  2. Cardio-Diagnostico, Paseo de los Heroes No. 2507, Zona Rio, Tijuana, Mexico

    German Prado-Arechiga

Authors
  1. Beatriz González
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  2. Patricia Melin
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  3. Fevrier Valdez
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  4. German Prado-Arechiga
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Corresponding author

Correspondence to Patricia Melin .

Editor information

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 , Warszawa, Poland

    Janusz Kacprzyk

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González, B., Melin, P., Valdez, F., Prado-Arechiga, G. (2018). Ensemble Neural Network Optimization Using a Gravitational Search Algorithm with Interval Type-1 and Type-2 Fuzzy Parameter Adaptation in Pattern Recognition Applications. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Studies in Computational Intelligence, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-71008-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-71008-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71007-5

  • Online ISBN: 978-3-319-71008-2

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