Neural network classification of extended control chart patterns

WSEAS Transactions on Computers

Volumn 6, Issue 1, 2007, Pages 160-166

  Watanapa, Bunthit ^a   Chan, Jonathan H ^a  

^a KING MONGKUT'S UNIVERSITY OF TECHNOLOGY THONBURI   (Thailand)

Author keywords

Bayesian regularization; Classification; Control chart patterns; Input delay; Levenberg Marquardt method; Neural networks; Principal component analysis; Time series data

Indexed keywords

BACKPROPAGATION; MATHEMATICAL MODELS; PRINCIPAL COMPONENT ANALYSIS; REAL TIME SYSTEMS; TIME DOMAIN ANALYSIS; TIME SERIES ANALYSIS;

BAYESIAN REGULARIZATION; CONTROL CHART PATTERNS; LEVENBERG-MARQUARDT METHOD; NEURAL NETWORK CLASSIFICATION; TIME SERIES DATA;

FEEDFORWARD NEURAL NETWORKS;

EID: 37849185794     PISSN: 11092750     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. K. Lavangnananda and A. Piyatumrong, "Utilizing Features Extraction in Classifying Control Chart Signals : A Synergistic Neural Networks Approach," 2004 International Conference on Advances in Intelligent Systems - Theory and Applications (AISTA2004), November 15-18, Centre de Recherche Public Henri Tudor, Luxembourg-Kirchberg, Luxembourg, 2004.
2. D.T. Pham and A.B. Chan, "Control Chart Pattern Recognition using a New Type of Self-Organising Network," Proc. Instn. Mech. Engs., Vol. 212, No. 1, 1998, pp. 115-127.
3. S. Sagiroglu, E. Besdok and M. Erler, "Control Chart Pattern Recognition Using Artificial Neural Networks," Turk J Elec Engin, Vol.8, No.2, 2000, pp. 137-147.
4. R.-S. Guh, Zorriassatine, F., Tannock, J.D.T. and O'Brien, C.O., "Online Control Chart Pattern Detection and Discrimination - A Neural Networks Approach", Artificial Intelligence in Engineering vol. 13, 1999, pp. 413-425.
5. C.M. Bishop, Neural Networks for Pattern Recognition, Oxford: Clarendon Press, 1995.
6. R.C. Rapaso and A.J. Cruz, "Stock Market Prediction Based on Fundamentalist Analysis with Fuzzy-Neural Networks," Proc. of the 3rd WSEAS Int. Conf. on Neural Networks and Applications (NNA'02), Interlaken, Switzerland, 12-14 February 2002, pp. 58-62.
7. D.T. Pham and S. Sagiroglu, "A Comparative Study of Four Multilayered Perceptron Training Algorithms," Int. Journal of Machine Tools and Manufacture, Vol. 41, 2001, pp. 419-430.
8. W. Klösgen and J.M. Zytkow, Handbook of Data Mining and Knowledge Discovery, Oxford University Press, 2002, pp. 214-218.
9. A. Nanopoulos, R. Alcock and Y. Manolopoulos, "Feature-Based Classification of Time-Series Data," in Information Processing and Technology, N. Mastorakis and S.D. Nikolopoulos, Eds., Nova Science Publishers, Cormack, NY, 2001, pp. 49-61.
10. W. DuMouchel and F. O'Brien, "Integrating a Robust Option into a Multiple Regression Computing Environment," in Computing Science and Statistics: Proceedings of the 21st Symposium on the Interface, (K. Berk and L. Malone, eds.), American Statistical Association, Alexandria, VA, 1989, pp. 297-301.
11. J.O. Street, R. J. Carroll, and D. Ruppert, "A Note on Computing Robust Regression Estimates via Iteratively Reweighted Least Squares," The American Statistician, vol. 42, 1988, pp. 152-154.
12. I.T. Jolliffe, Principal Component Analysis, New York: Springer-Verlag, 1986.
13. M.T. Hagan and M. Menhaj, "Training feedforward networks with the Marquardt algorithm," IEEE Transactions on Neural Networks, vol. 5, no. 6, 1994, pp. 989-993.
14. F.D. Foresee and M. T. Hagan, "Gauss-Newton approximation to Bayesian regularization," Proceedings of the 1997 International Joint Conference on Neural Networks (IJCNN'97), Houston, Texas, USA, 1997, pp. 1930-1935.
15. K. Lavangnananda, and O. Tengsriprasert, "Classification of Time Series Data: A Synergistic Neural networks Approach", Proceedings of the 9th International Conference on Neural Information Processing (ICONIP'02), 18-22 November, Singapore, Vol. 1, 2002, pp. 179-183.