Support vector regression for structural identification via component-mode synthesis

DOI QR Code

Zhang, J. (Department of Structural Engineering, University of California) ;
Sato, T. (Section of Disaster Management and Social Service, Kobegakuin University) ;
Iai, S. (Department of Civil and Earth Resources Engineering, Kyoto University)

Cherkassky, V. and Ma, Y. (2004), 'Practical selection of SVM parameters and noise estimation for SVM regression', Neural Networks, 17, 113-126 https://doi.org/10.1016/S0893-6080(03)00169-2
Morales, C.A. (2000), 'Dynamic analysis of frames by a Rayleigh-Ritz based component mode method', Eng. Struct., 22, 1632-1640 https://doi.org/10.1016/S0141-0296(99)00113-3
Takewaki, I. and Uetani, K. (2000), 'Inverse component-mode synthesis method for damped large structural systems', Comput. Struct., 78, 415-423 https://doi.org/10.1016/S0045-7949(00)00088-2
Vapnik, V.N. (1999), The Nature of Stastical Learning Theory, 2nd edn., Springer-Verlag
Zhang, J., Sato, T. and Iai, S. (2006), 'Large-scale structural health monitoring by increment support vector regression with local strategy', J. Struct. Safety, 28, 392-406 https://doi.org/10.1016/j.strusafe.2005.12.001