Combining Use of Rough Set and Artificial Neural Networks in Doweled-Pavement-Performance Modeling—A Hybrid Approach
Publication: Journal of Transportation Engineering
Volume 128, Issue 3
Abstract
This paper explores the potential applications of rough set theory and neural networks in concrete-faulting-performance modeling. The rough set can be used to reduce the dimension of the original pavement database in terms of attributes and rows. The reduced table can then be used as an input into the neural network. Since there are no universal rules for neural network construction, this approach is very important. Constructive and destructive methods have been used in the construction of neural network architecture. Although these methods are appropriate, they do not have a strong scientific proof. The key characteristics of the proposed method is that the new decision table created by using the rough set analysis will free the neural network paradigm from redundancy. A simple example for faulting performance in concrete pavement is presented.
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References
Ahn, B. S., Cho, S. S., and Kim, C. Y.(2000). “The integrated methodology of rough set theory and artificial neural network for business failure prediction.” Expert Sys. Applic., 18, 65–74.
An, A. J., et al. (1996). “Discovering rules for water demand prediction: An enhanced rough set approach.” Eng. Applic. Artif. Intell., 9(6), 645–653.
Armaghani, J. M.(1993). “Factors affecting performance of concrete pavements.” Proc., 5th Int. Conf. Concrete Pavement Design and Rehabilitation, Purdue Univ., West Lafayette, Ind., 1, 33–46.
Attoh-Okine, N. O., and Moore, R. K. (1993). “The effect of dowels on the performance of concrete pavements in Kansas.” K-TRAN Project 93-6, interim report presented to Kansas Dept. of Transportation, 61.
Attoh-Okine, N. O. (1994). “Predicting roughness progression in flexible pavements using artificial neural networks.” Proc., 3rd Int. Conf. Managing Pavements, San Antonio, Tex., 52–62.
Attoh-Okine, N. O.(1997). “Rough set application to data mining principles in pavement management database.” J. Comput. Civ. Eng., 11(4), 231–237.
Attoh-Okine, N. O.(1999). “Analysis of learning rate and momentum term in backpropagation neural network algorithm trained to predict pavement performance.” Adv. Eng. Software, 30(4), 293–302.
Attoh-Okine, N. O. (2000). “Grouping pavement condition variables for performance modeling using self-organizing maps.” Comput.-Aided Civ. Infrastruct. Eng.
Carey, W. N., and Irick, P. E. (1960). “The pavement serviceability-performance concept.” Bulletin 250, HRB, National Research Council, Washington, D.C. 40–58.
Darter, M, Smith, K. D., and Peshkin, D. G. (1991). “Field-calibrated mechanistic models for jointed pavement.” Transportation Research Record No. 1307, 143–153.
Fwa, T. F., and Chan, W. T.(1993). “Priority rating of highway maintenance need by neural networks.” J. Transp. Eng., 119(3), 419–432.
Haas, R., Hudson, W. R., and Zaniewski, J. (1994). Modern pavement management, Krieger.
Hewitson, B. C., and Crane, R. G. (1994). Neural nets: Applications in Geography, Kluwer Academic, Dordrecht, The Netherlands.
Huang, Y., and Moore, R. K. (1997). “POS distress level probability prediction in PMS using ANNs.” Paper No. 97-0419, presented at Transportation Research Board, Washington, D.C.
Ioannides, A. M., Lee, Y. H., and Darter, M. (1990). “Control of faulting through joint load transfer design.” Transportation Research Record No. 1286, National Research Council, Washington, D.C., 49–56.
Jelonek, J., Krawiec, K., and Slowinski, R.(1995). “Rough set reduction of attributes and their domains for neural nets.” Comput. Intell., 11(2), 339–347.
Kryszkiewicz, M. (1998). “Chapter 21: Properties of incomplete information systems in the framework of rough sets.” Rough set and Knowledge Discovery, L. Polliowski and A. Skowron, eds., 422–450.
Kryszkiewicz, M.(1999). “Rules in incomplete information systems.” Information Sciences, 113, 271–292.
Lukanen, E. O., and Han, C.(1994). “Performance history and prediction modeling for Minnesota pavements.” Proc., 3rd Int. Conf. Managing Pavements, 1, 63–73.
Nabhan, M. Y., and Zomaya, A. Y.(1994). “Toward generating neural network structures for function approximation.” Neural Network, 7(1), 89–99.
Nelson, M. M., and Illingworth, W. T. (1989). A practical guide to neural net, Texas Instruments, Dallas, Tex.
Nigyuan, Li., Haas, R., and Xie, L. (1997). “Investigation of the relationship between deterministic and probabilistic prediction models in pavement management.” Paper No. 970171, presented at the Annual Transportation Research Board, Washington, D.C.
Pawlak, Z. (1991). Rough sets: Theoretical aspects of reasoning about data, Kluwer Academic, Boston.
Reed, R. D., and Marks, R. (1999). Neural smithing, MIT, Cambridge, Mass.
Roberts, C. A., and Attoh-Okine, N. O.(1998). “A comparative analysis of two artificial neural networks using pavement performance prediction.” Comput.-Aided Civ. Infrastruct. Eng., 13, 339–348.
Simpson, A. L., et al. (1994). “Sensitivity analyses for selected pavement distresses.” SHRP-P-393 Rep., National Research Council, Washington D.C.
Skowron, A.(1995). “Extracting laws from decision tables.” Comput. Intelligence, 11(2), 371–388.
Snyder, M., and Darter, M. (1989). “Design procedure for dowel load-transfer systems for full-depth repair joints.” Transportation Research Record No. 1272, National Research Council, Washington, D.C., 50–64.
Szczuka, M.(1996). “Rough set methods for constructing artificial neural networks.” Eng. Sys. Des. Anal., 7, 9–14.
Tsumoto, S.(1998). “Automated extraction of medical expert systems rules from clinical databases based on rough set theory.” Information Sciences, 112, 67–84.
Wu, C. L., et al. (1993). “Prediction of faulting of joints in concrete pavements.” Proc., 5th Int. Conf. Concrete Pavement Design and Rehabilitation, Purdue Univ., West Lafayette, Ind., 2, 53–70.
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Published In
Journal of Transportation Engineering
Volume 128 • Issue 3 • May 2002
Pages: 270 - 275
Copyright
Copyright © 2002 American Society of Civil Engineers.
History
Received: Oct 27, 2000
Accepted: Jun 27, 2001
Published online: Apr 15, 2002
Published in print: May 2002
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