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Advance Trends in Soft Computing pp 347–356Cite as

Automatic Sintonization of SOM Neural Network Using Evolutionary Algorithms: An Application in the SHM Problem

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 312))

Abstract

This paper is a contribution to the Structural Health Monitoring problem, solved by using case based reasoning and Self Organizing Maps. The expert system described in this paper is able to detect, locate and quantify stiffness percentage changes in a mechanical engineering structure. In order to overcome issues relating large number of parameters involved in the training stage it was applyed differential evolutive algorithms. Proper indexes to evaluate the training quality were proposed in order to increase diagnosis reliability. The algorithms were tested using the UBC ASCE Benchmark. The numerical implementation shows decreasing in the identification errors with respect to those obtained by selecting manually network training parameters.

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References

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Author information

Authors and Affiliations

  1. Escuela de Ingenierías Eléctrica, Electrónica y de Telecomunicaciones, Universidad Industrial de Santander, Grupo CEMOS. UIS. E3T., Carrera 27, calle 9, Ciudad UniversitariaBucaramanga, Colombia

    Rodolfo Villamizar, Jhonatan Camacho, Yudelman Carrillo & Leonardo Pirela

Authors
  1. Rodolfo Villamizar
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  2. Jhonatan Camacho
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  3. Yudelman Carrillo
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  4. Leonardo Pirela
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Corresponding author

Correspondence to Rodolfo Villamizar .

Editor information

Editors and Affiliations

  1. The University of Texas, San Antonio, Texas, USA

    Mo Jamshidi

  2. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

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

    Janusz Kacprzyk

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© 2014 Springer International Publishing Switzerland

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Villamizar, R., Camacho, J., Carrillo, Y., Pirela, L. (2014). Automatic Sintonization of SOM Neural Network Using Evolutionary Algorithms: An Application in the SHM Problem. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_33

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  • DOI: https://doi.org/10.1007/978-3-319-03674-8_33

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03673-1

  • Online ISBN: 978-3-319-03674-8

  • eBook Packages: EngineeringEngineering (R0)

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