A hybrid neural network strategy for identification of structural parameters

Structure and Infrastructure Engineering

Volumn 6, Issue 3, 2010, Pages 379-391

  Pillai, Prashanth ^a   Krishnapillai, Shankar ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

Backpropagation network; Counterpropagation network; Levenberg Marquardt method

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; BACKPROPAGATION NETWORK; CENTRAL PROCESSING UNITS; COMPUTATIONAL EFFORT; COUNTER PROPAGATION NETWORKS; COUNTER PROPAGATION NEURAL NETWORKS; DAMAGE ASSESSMENTS; DAMAGE EXTENT; DAMAGE IDENTIFICATION; DAMAGE PATTERNS; DIFFERENT DAMAGES; HYBRID NEURAL NETWORKS; IDENTIFICATION SCHEME; LARGE STRUCTURES; LEVENBERG-MARQUARDT ALGORITHM; LEVENBERG-MARQUARDT METHOD; MODAL DATA; NUMERICAL EXAMPLE; REDUCED SIZE; STRUCTURAL DAMAGE DETECTION; STRUCTURAL PARAMETER; TRAINING DATA; TRAINING DATA SETS; TRAINING PATTERNS;

BACKPROPAGATION; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; LEARNING ALGORITHMS; MODAL ANALYSIS; NEURAL NETWORKS; PROGRAM PROCESSORS; STRUCTURAL ANALYSIS;

DAMAGE DETECTION;

EID: 77951647962     PISSN: 15732479     EISSN: 17448980     Source Type: Journal    
DOI: 10.1080/15732470701718197     Document Type: Article

References (24)

1. Adeli, H. and Park, H.S., 1995. Counterpropagation neural networks in structural engineering. Journal of structural engineering, 121, 1205-1212.
2. Barai, S.V. and Pandey, P.C., 1995. Vibration signature analysis using artificial neural networks. Journal of computing in civil engineering, 9, 259-265.
3. Caravani, P., Watson, M.L., and Thomson, W.T., 1997. Recursive least-squares time domain identification of structural parameters. Journal of applied mechanics, 44, 135-140.
4. Ceravolo, R., de Stefano, A., and Sabia, D., 1995. Hierarchical use of neural techniques in structural damage recognition. Smart materials structure, 4, 270-280.
5. Costa, M.A., de Padua Braga, A., and de Menezes, B.R., 2007. Improving generalisation of MLPs with sliding mode control and the Levenberg-Marquardt algorithm. Neurocomputing, 70 (7-9), 1342-1347.
6. Elkordy, M.F., Chang, K.C., and Lee, G.C., 1993. Neural networks trained by analytically simulated damaged states. Journal of computing in civil engineering, 7, 130-145.
7. Fang, X., Luo, H., and Tang, J., 2005. Structural damage detection using neural network with learning rate improvement. Computers and structures, 83 (25-26), 2150-2161.
8. Fausett, L., 1994. Fundamentals of neural networks - architectures, algorithms and applications. Prentice Hall Inc.
9. Hagan, M.T. and Menhaj, M., 1994. Training feedforward networks with the Marquardt algorithm. IEEE transactions neural networks, 5, 989-993.
10. Hecht-Nielsen, R., 1987. Counterpropagating networks. Applied optics, 26, 4979-4984.
11. Kermani, B.G., Schiffman, S.S., and Nagle, H.T., 2005. Performance of the Levenberg-Marquardt neural network training method in electronic nose applications. Sensors and actuators, 110, 13-22.
12. Ko, J.M., Sun, Z.G., and Ni, Y.Q., 2002. Multistage identification scheme for detecting damage in cablestayed Kap Shui Mun Bridge. Engineering structures, 24, 857-868.
13. Lam, H.F., Ko, J.M., and Wong, C.W., 1998. Localization of damaged structural connections based on experimental modal and sensitivity analysis. Journal of sound and vibration, 210, 91-115.
14. Levenberg, K., 1944. A method for the solution of certain problems in least squares. Quarterly of applied mathematics, 2, 164-168.
15. Madan, A., 2005. Vibration control of building structures using self-organizing and self-learning neural networks. Journal of sound and vibration, 287, 759-784.
16. Ni, Y.Q., Wang, B.S., and Ko, J.M., 2002. Constructing input vectors to neural networks for structural damage identification. Smart materials and structures, 11, 825-833.
17. Pandey, P.C. and Barai, S.V., 1995. Multilayer perceptron in damage detection of bridge structures. Computers and structures, 54 (4), 597-608.
18. Shinozuka, M., Yun, C.B., and Imai, H., 1982. Identification of linear structural dynamic system. Journal of engineering mechanics, ASCE, 108, 1371-1390.
19. Singh, V., Gupta, I., and Gupta, H.O., 2007. ANN-based estimator for distillation using Levenberg-Marquardt approach. Engineering applications of artificial intelligence, 20, 249-259.
20. Szewczyk, Z.P. and Hajela, P., 1994. Damage detection in structures based on feature sensitive neural networks. Journal of computing in civil engineering, 8 (2), 163-179.
21. Vora, N., Tambe, S.S., and Kulkarni, B.D., 1997. Counterpropagation neural networks for fault detection and diagnosis. Computers in chemical engineering, 21 (2), 177-185.
22. Wu, X., Ghaboussi, J., and Garrett, J.H., 1992. Use of neural networks in detection of structural damage. Computers and structures, 42 (4), 649-659.
23. Yun, C.B., Kim, W.J., and Ang, A.H.S., 1988. Damaged assessment of bridge structures by system identification. In: Proceedings of Korea-Japan joint seminar on emerging technology in structural engineering and mechanics, 182-193.
24. Zhao, J., John, N.I., and deWolf, J.T., 1998. Structural damage detection using artificial neural networks. Journal of infrastructure systems, 4 (3), 93-101.