424
Views
11
CrossRef citations to date
0
Altmetric
Articles

Structural damage diagnosis using incomplete static responses and LS-SVM

Pages 418-433 | Received 10 Feb 2015, Accepted 18 Mar 2016, Published online: 31 Mar 2016

References

  • He RS, Hwang SF. Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis. Eng. Appl. Artif. Intell. 2007;20:980–992.10.1016/j.engappai.2006.11.020
  • Kourehli SS. LS-SVM regression for structural damage diagnosis using the iterated improved reduction system. Int. J. Struct. Stab. Dy. 2016;16:1550018. doi:10.1142/S0219455415500182.
  • Kourehli SS. Damage assessment in structures using incomplete modal data and artificial neural network. Int. J. Struct. Stab. Dyn. 2015;15:1450087. doi:10.1142/S0219455414500874.
  • Rasouli A, Ghodrati Amiri G, Kheyroddin A, et al. A new method for damage prognosis based on incomplete modal data via an evolutionary algorithm. Eur. J. Environ. Civil Eng. 2014;18:253–270.10.1080/19648189.2014.881758
  • Kourehli SS, Bagheri A, Ghodrati Amiri G, et al. Structural damage identification method based on incomplete static responses using an optimization problem. Sci. Iran. 2014;21:1209–1216.
  • Wang X, Hu N, Fukunaga H, et al. Structural damage identification using static test data and changes in frequencies. Eng. Struct. 2001;23:610–621.10.1016/S0141-0296(00)00086-9
  • Wang X, Yang H, Wang L, et al. Interval analysis method for structural damage identification based on multiple load cases. J. Appl. Mech. 2012;79:051010.10.1115/1.4006447
  • Abdo MAB. Parametric study of using only static response in structural damage detection. Eng. Struct. 2012;34:124–131.10.1016/j.engstruct.2011.09.027
  • Viola E, Bocchini P. Non-destructive parametric system identification and damage detection in truss structures by static tests. Struct. Infrastruct. Eng. 2013;9:384–402.10.1080/15732479.2011.560164
  • Suykens JAK, Vandewalle J. Least squares support vector machine classifiers. Neural Process. Lett. 1999;9:293–300.10.1023/A:1018628609742
  • Xie JH. Structural damage detection based on fuzzy LS-SVM integrated quantum genetic algorithm. Appl. Mech. Mater. 2010;20:1365–1371.10.4028/www.scientific.net/AMM.20-23
  • Xie J. Improved least square support vector machine for structural damage detection. Neural Comput. 2010;6:V6-237–V6-240.
  • Tang HS, Xue ST, Chen R, et al. Online weighted LS-SVM for hysteretic structural system identification. Eng. Struct. 2006;28:1728–1735.10.1016/j.engstruct.2006.03.008
  • Szewczyk ZP, Hajela P. Damage detection in structures based on feature-sensitive neural networks. J. Comput. Civil Eng. 1994;8:163–178.10.1061/(ASCE)0887-3801(1994)8:2(163)
  • Cristianini N, Shawe-Taylor J. An introduction to support vector machines. Cambridge: Cambridge University Press; 2000.
  • Suykens JAK, Van Gestel T, De Brabanter J, et al. Least squares support vector machines. Singapore: World Scientific; 2002.
  • Keerthi SS, Lin CJ. Asymptotic behaviors of support vector machines with Gaussian Kernel. Neural Comput. 2003;15:1667–1689.10.1162/089976603321891855
  • Xavier-de-Souza S, Suykens JA, Vandewalle J, et al. Coupled simulated annealing. IEEE Trans. Syst. Man Cybernet. Part B. 2010;40:320–335.10.1109/TSMCB.2009.2020435
  • Sun B, Ng WW, Yeung DS, et al. Hyper-parameter selection for sparse LS-SVM via minimization of its localized generalization error. Int. J. Wavelets Multiresolut. Inf. Process. 2013;11:1350030.10.1142/S0219691313500306
  • De Brabanter K, Karsmakers P, Ojeda F, et al. LS-SVMlab toolbox user’s guide. Leuven: ESAT-SISTA Technical Report; 2011. p. 10–146.
  • Available from. http://www.esat.kuleuven.be/sista/lssvmlab/.
  • MATLAB. Matlab user manual. Lowell (MA): Mathwork ; 2013.
  • Rumelhart DE, McClell JL. Parallel distributed processing, foundations. Vol. 1. Cambridge, MA: MIT Press; 1986.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.