Artmap-fuzzy artificial neural network applied in recognition of structural faults

Authors

  • Jacqueline S. Chaves Universidade Estadual Paulista (UNESP)
  • Mara Lúcia M. Lopes Universidade Estadual Paulista (UNESP)
  • Fábio Roberto Chavarette Universidade Estadual Paulista (UNESP)
  • Fernando Parra Dos Anjos Lima Universidade Estadual Paulista (UNESP)

DOI:

https://doi.org/10.5944/ribim.21.1.42358

Keywords:

Artificial Neural Networks, Fault Recognition, ARTMAP-Fuzzy

Abstract

In order to develop an efficient way to identify and characterize structural faults, this paper aimed to demonstrate an application of Artificial Neural Networks (ANNs) for this problem. Therefore, through a dynamic model for the representation of a building structure, an ARTMAP-Fuzzy RNA has been developed because it is a flexible and stable network in relation to its ability to adapt to unforeseen changes in the external environment to identify such failures

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Published

2017-04-01

How to Cite

Chaves, J. S. ., Lopes, M. L. M. ., Chavarette, F. R. ., & Lima, F. P. D. A. . (2017). Artmap-fuzzy artificial neural network applied in recognition of structural faults. Revista Iberoamericana de Ingeniería Mecánica, 21(1), 3–11. https://doi.org/10.5944/ribim.21.1.42358

Issue

Vol. 21 No. 1 (2017)

Section

Articles

License


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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