A hybrid Bayesian back-propagation neural network approach to multivariate modelling

International Journal for Numerical and Analytical Methods in Geomechanics

Volumn 27, Issue 8, 2003, Pages 651-667

  Chua, C G ^a   Goh, A T C ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Back propagation neural network; Bayesian neural network; Genetic algorithms; Neural network; Non linear modelling; Piling; Skin friction

Indexed keywords

BACKPROPAGATION; GENETIC ALGORITHMS; NEURAL NETWORKS; NONLINEAR SYSTEMS; RANDOM PROCESSES;

MULTIVARIATE PROBLEMS;

GEOTECHNICAL ENGINEERING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; GEOTECHNICAL ENGINEERING; MULTIVARIATE ANALYSIS; NONLINEARITY;

EID: 0041310976     PISSN: 03639061     EISSN: None     Source Type: Journal    
DOI: 10.1002/nag.291     Document Type: Article

References (36)

1. Goh ATC. Seisimic liquefaction potential assessed by neural networks. Journal of Geotechnical Engineering, ASCE 1994; 120(9):1467-1480.
2. Juang CH, Chen CJ, Tien YM. Appraising CPT-based liquefaction resistance evaluation methods-artificial neural network approach. Canadian Geotechnical Journal, 1999; 36(3):443-454.
3. Goh ATC. Empirical design in geotechnics using neural networks. Geotechnique 1995; 45(4):709-714.
4. Nawari NO, Liang R. Intelligent hybrid system for the design of pile foundations. In New Technological and Design Developments in Deep Foundations, Dennis, ND Jr., Castelli R, O'Neill MW (eds). ASCE Geotechnical Special Publication No. 100: New York, 2000; 312-326.
5. Ghaboussi J, Garrett JH Jr., Wu X. Knowledge-based modelling of material behavior with neural networks. Journal of Engineering Mechanics, ASCE 1991; 117(1):132-153.
6. Ellis GW, Yao C, Zhao R, Penumadu D. Stress-strain modelling of sands using artificial neural networks. Journal of Geotechnical Engineering, ASCE 1995; 121(5):429-435.
7. Najjar Y, Zhang XC. Characterizing the 3-D stress-strain behavior of sandy soils. A neuro-mechanistic approach. In Numerical Methods in Geotechnical Engineering, Filz GM, Grifiths DV (eds). ASCE Geotechnical Special Publication No. 96: New York, 2000; 43-57.
8. Rumelhart DE, Hinton GE, Williams RJ. Learning internal representation by error propagation. In Parallel Distributed Processing, Rumelhart DE, McClelland JL (eds). MIT Press: Cambridge, 1986; 1:318-362.
9. Hornik K. Approximation capabilities of multiplayer feedfoward networks. Neural Networks 1991; 4(2):251-257.
10. Caudill M, Butler C. Naturally Intelligent Systems. MIT Press: Cambridge, 1991.
11. Eberhart RC, Dobbins RW. Neural Network PC tools: A Practical Guide. Academic Press: San Diego, 1990.
12. Bishop CM. Neural Networks for Pattern Recognition. Oxford University Press: Oxford, 1995.
13. Hassoun MH. Fundamentals of Artificial Neural Networks. MIT Press: Cambridge, 1995.
14. Masri SF, Smyth AW, Chassiakos AG, Nakamura M, Caughey TK. Training neural networks by adaptive random search techniques. ASCE Journal of Engineering Mechanics 1999; 125(2):123-132.
15. Gori M, Tesi A. On the problem of local minimum in backpropagation. Transactions on Pattern Analysis and Machine Learning, IEEE 1992; 14(1):76-86.
16. Mackay DJC. Bayesian methods for adaptive models. PhD Thesis, California Institute of Technology, 1991.
17. Neal RM. Bayesian training of back-propagation networks by the hybrid Monte Carlo method. Technical Report CRG-TG-92-1, Department of Computer Science, University of Toronto, 1992.
18. Box GEP, Tiao GC. Bayesian Inference in Statistical Analysis. Addison-Wesley: Reading, 1973.
19. Gull SF. Bayesian inductive inference and maximum entropy. In Maximum Entropy and Bayesian Methods in Science and Engrg., Foundations, vol. 1, Ericson GJ, Smith CR (eds). Kluwer: Norwell 1988; 53-74.
20. Mackay DJC. Bayesian interpolation. Neural Computation 1992; 4(3):415-447.
21. Thodberg HH. A review of Bayesian neural networks with an application to near infrared spectroscopy. Transactions on Neural Networks, IEEE 1996; 7(1):56-72.
22. Mackay DJC. Bayesian non-linear modelling for the prediction competition. ASHRAE Transactions 1995; 100(2):1053-1062.
23. Holland JH. Adaptation in Natural and Artificial Systems. University of Michigan Press: Ann Arbor, 1975.
24. Goldberg DE. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley: Reading, MA, 1989.
25. Chua CG, Goh ATC. Evolutionary Bayesian Back-propagation-an artificial neural network program. Geotechnical Research Report No. NTU/GT/2001-1, Nanyang Technological University: Singapore, 2001.
26. De Jong K. An analysis of the behavior of a class of genetic adaptive systems. Ph.D Thesis, Department of Computer and Communications Sciences, University of Michigan, Ann Arbor, 1975.
27. Nguyen D, Widrow B. Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights. Proceedings of the International Joint Conference on Neural Networks, San Diego, IEEE 1990; 3:21-26.
28. Metroplis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E. Equation of state calculations by fast computing machines. Journal of Chemical Physics 1953; 21(6):1087-1092.
29. Vonk E, Jain LC, Johnson RP. Automatic Generation of Neural Network Architecture using Evolutionary Computation. World Scientific: Singapore, 1997.
30. Bathe KJ. Finite Element Procedures. Prentice-Hall: NJ, 1996.
31. Choueiki MH, Mount-Campbell CA. Training data development with the D-optimality criterion. Transactions on Neural Networks, IEEE 1999; 10(1):56-63.
32. Tomlinson MJ. Adhesion of piles driven in clay soils. Proceedings of the 4th International Conference on Soil Mechanics and Foundation Engineering, vol. 2, London, 1957; 66-71.
33. Randolph MF, Murphy BS. Shaft capacity of driven piles in clay. Proceedings of the 17th Offshore Technology Conference, Houston, 1985; 371-378.
34. Semple RM, Ridgen WJ. Shaft capacity of driven pipe piles in clay. Ground Engineering 1986; 19(1):11-17.
35. Vijayvergiya VN, Focht, JA Jr. A new way to predict capacity of piles in clay. Proceedings of the 4th Offshore Technology Conference, vol. 2, Houston, 1972; 865-874.
36. Flaate K, Selnes P. Side friction of piles in clay. Proceedings of the 9th International Conference on Soil Mechanics and Foundation Engineering, vol. 1, Tokyo, 1977; 517-522.