-
1
-
-
0021593866
-
Structural identification by extended Kalman filter
-
Hoshiya M. Structural identification by extended Kalman filter. Journal of Engineering Mechanics 1984; 110: 1757-1770.
-
(1984)
Journal of Engineering Mechanics
, vol.110
, pp. 1757-1770
-
-
Hoshiya, M.1
-
2
-
-
0033924442
-
Structural identification of frames under earthquake loading - time domain identification algorithms
-
Loh CH, Lin CY, Huang CC. Structural identification of frames under earthquake loading - time domain identification algorithms. Journal of Engineering Mechanics 2000; 126:693-703.
-
(2000)
Journal of Engineering Mechanics
, vol.126
, pp. 693-703
-
-
Loh, C.H.1
Lin, C.Y.2
Huang, C.C.3
-
3
-
-
0032207048
-
∞ filter: Its application to structural identification
-
∞ filter: its application to structural identification. Journal of Engineering Mechanics 1998; 124:1233-1240.
-
(1998)
Journal of Engineering Mechanics
, vol.124
, pp. 1233-1240
-
-
Sato, T.1
Qi, K.2
-
4
-
-
28244444895
-
Health monitoring algorithm by the Monte-Carlo filter based on non-Gaussian noise
-
Yoshida I, Sato T. Health monitoring algorithm by the Monte-Carlo filter based on non-Gaussian noise. Journal of Natural Disaster Science 2002; 24:101-107.
-
(2002)
Journal of Natural Disaster Science
, vol.24
, pp. 101-107
-
-
Yoshida, I.1
Sato, T.2
-
5
-
-
0033737832
-
Substructural identification using neural networks
-
Yun CB, Bahng EY. Substructural identification using neural networks. Computers and Structures 2000; 77:41-52.
-
(2000)
Computers and Structures
, vol.77
, pp. 41-52
-
-
Yun, C.B.1
Bahng, E.Y.2
-
8
-
-
0016939287
-
Method of random vibration of hysteretic systems
-
Wen YK. Method of random vibration of hysteretic systems. Journal of Engineering Mechanical Division 1976; 102:249-263.
-
(1976)
Journal of Engineering Mechanical Division
, vol.102
, pp. 249-263
-
-
Wen, Y.K.1
-
9
-
-
3042512063
-
Analysis and modification of Volterra/Wiener neural networks for the adaptive identification of non-linear hysteretic dynamic systems
-
Pei JS, Smyth AW, Kosmatopoulos EB. Analysis and modification of Volterra/Wiener neural networks for the adaptive identification of non-linear hysteretic dynamic systems. Journal of Sound and Vibration 2004; 275:693-718.
-
(2004)
Journal of Sound and Vibration
, vol.275
, pp. 693-718
-
-
Pei, J.S.1
Smyth, A.W.2
Kosmatopoulos, E.B.3
-
10
-
-
0028977380
-
Identification of hysteretic oscillators under earthquake loading by nonparametric models
-
Benedettini F, Capecchi D, Vestroni F. Identification of hysteretic oscillators under earthquake loading by nonparametric models. Journal of Engineering Mechanics 1995; 121:606-612.
-
(1995)
Journal of Engineering Mechanics
, vol.121
, pp. 606-612
-
-
Benedettini, F.1
Capecchi, D.2
Vestroni, F.3
-
11
-
-
0030107486
-
Identification of dynamic properties of isolated structures
-
Tan RY, Weng IW. Identification of dynamic properties of isolated structures. Engineering Structures 1996; 18:240-246.
-
(1996)
Engineering Structures
, vol.18
, pp. 240-246
-
-
Tan, R.Y.1
Weng, I.W.2
-
12
-
-
0035935966
-
Identification of hysteretic systems using the differential evolution algorithm
-
Kyprianou A, Worden KK, Panet M. Identification of hysteretic systems using the differential evolution algorithm. Journal of Sound and Vibration 2001; 248:289-314.
-
(2001)
Journal of Sound and Vibration
, vol.248
, pp. 289-314
-
-
Kyprianou, A.1
Worden, K.K.2
Panet, M.3
-
14
-
-
0032487707
-
Identification of non-linear hysteretic isolators from periodic vibration tests
-
Ni YQ, Ko JM, Wong CW. Identification of non-linear hysteretic isolators from periodic vibration tests. Journal of Sound and Vibration 1998; 217:737-756.
-
(1998)
Journal of Sound and Vibration
, vol.217
, pp. 737-756
-
-
Ni, Y.Q.1
Ko, J.M.2
Wong, C.W.3
-
16
-
-
0025453740
-
Sequential parametric identification and response of hysteretic oscillators with random excitation
-
Roberts JB, Sadeghi AH. Sequential parametric identification and response of hysteretic oscillators with random excitation. Structural Safety 1990; 8:45-68.
-
(1990)
Structural Safety
, vol.8
, pp. 45-68
-
-
Roberts, J.B.1
Sadeghi, A.H.2
-
18
-
-
2442436686
-
On-line identification of non-linear hysteretic structures using an adaptive tracking technique
-
Jann JN, Yang N, Lin S. On-line identification of non-linear hysteretic structures using an adaptive tracking technique. International Journal of Non-linear Mechanics 2004; 39:1481-1491.
-
(2004)
International Journal of Non-linear Mechanics
, vol.39
, pp. 1481-1491
-
-
Jann, J.N.1
Yang, N.2
Lin, S.3
-
21
-
-
33745199865
-
Support vector regression for on-line health monitoring of large-scale structures
-
Zhang J, Sato T, Iai S. Support vector regression for on-line health monitoring of large-scale structures. Structural Safety 2006; 28:392-406.
-
(2006)
Structural Safety
, vol.28
, pp. 392-406
-
-
Zhang, J.1
Sato, T.2
Iai, S.3
-
22
-
-
11244288369
-
Automatic model selection: A new instrument for social science
-
Hendry DF, Krolzig HM. Automatic model selection: a new instrument for social science. Electoral Studies 2004; 23:525-544.
-
(2004)
Electoral Studies
, vol.23
, pp. 525-544
-
-
Hendry, D.F.1
Krolzig, H.M.2
-
23
-
-
22844442782
-
Automatic model selection for the optimization of SVM kernels
-
Ayat NE, Cheriet M, Suen CY. Automatic model selection for the optimization of SVM kernels. Pattern Recognition 2005; 38:1733-1745.
-
(2005)
Pattern Recognition
, vol.38
, pp. 1733-1745
-
-
Ayat, N.E.1
Cheriet, M.2
Suen, C.Y.3
-
25
-
-
0003425664
-
Support vector machines for classification and regression
-
Technical Report, University of Southampton
-
Gunn SR. Support vector machines for classification and regression. Technical Report, University of Southampton, 1998.
-
(1998)
-
-
Gunn, S.R.1
-
27
-
-
0141765796
-
Accurate on-line support vector regression
-
Ma J, Theiler J, Perkins S. Accurate on-line support vector regression. Neural Computation 2003; 15:2683-2703.
-
(2003)
Neural Computation
, vol.15
, pp. 2683-2703
-
-
Ma, J.1
Theiler, J.2
Perkins, S.3
-
28
-
-
0346250790
-
Practical selection of SVM parameters and noise estimation for SVM regression
-
Cherkassky V, Ma Y. Practical selection of SVM parameters and noise estimation for SVM regression. Neural Networks 2004; 17:113-126.
-
(2004)
Neural Networks
, vol.17
, pp. 113-126
-
-
Cherkassky, V.1
Ma, Y.2
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