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Damage evaluation through radial basis function network based artificial neural network scheme

  • Lakshmanan, N. (Structural Engineering Research Centre, CSIR Campus) ;
  • Raghuprasad, B.K. (Department of Civil Engineering, Indian Institute of Science) ;
  • Muthumani, K. (Structural Engineering Research Centre, CSIR Campus) ;
  • Gopalakrishnan, N. (Structural Engineering Research Centre, CSIR Campus) ;
  • Basu, D. (Structural Engineering Research Centre, CSIR Campus)
  • Received : 2006.07.13
  • Accepted : 2007.08.10
  • Published : 2008.01.25

Abstract

Keywords

References

  1. Jang, J. S. R., Sun, C. T. and Mizutani, E. (1989), Neuro-Fuzzy and soft computing - A computational approach to learning and machine intelligence, Prentice Hall, New Jersey.
  2. Powell, M. J. D. (1987), "Radial basis functions for multi-variable interpolation - A Review", Algorithms for Approximations, Oxford University Press, 143-167.
  3. Karray, F. O. and De Silva, C. (2004), Soft Computing and Intelligent System Design, Pearson Education, Essex, England.
  4. MATLAB-7, Mathworks Inc, Natick, MA.

Cited by

  1. Modal parameters based structural damage detection using artificial neural networks - a review vol.14, pp.2, 2014, https://doi.org/10.12989/sss.2014.14.2.159
  2. Detection of local matrix cracks in composite beam using modal data and modular radial basis neural networks vol.6, pp.2, 2017, https://doi.org/10.1007/s41683-017-0013-z
  3. Smart pattern recognition of structural systems vol.6, pp.1, 2008, https://doi.org/10.12989/sss.2010.6.1.039