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Mathematical Formulation of a Type of Hierarchical Neurofuzzy System

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4253))

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Abstract

This paper presents a class of hierarchical fuzzy system applied to a cigar classification system. The weight, texture and chromatic characteristics are used to classify multiple cigars using a previous classification based on heuristic knowledge. In the adaptive part, a gradient descendent and error backpropagation method is applied for adjusting the parameters. A detailed description of the algorithm is addressed. Copyright © 2005 IFAC.

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References

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Author information

Authors and Affiliations

  1. Escuela Politécnica Superior, Huelva University, Ctra. Palos de la Frontera-Huelva, 21819, La Rábida (Huelva), Spain

    Omar Sánchez, Sixto Romero, Francisco Moreno & Miguel A. Vélez

Authors
  1. Omar Sánchez
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  2. Sixto Romero
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  3. Francisco Moreno
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  4. Miguel A. Vélez
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Sánchez, O., Romero, S., Moreno, F., Vélez, M.A. (2006). Mathematical Formulation of a Type of Hierarchical Neurofuzzy System. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_52

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  • DOI: https://doi.org/10.1007/11893011_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46542-3

  • Online ISBN: 978-3-540-46544-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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