Priority Rating of Highway Maintenance Needs by Neural Networks
Publication: Journal of Transportation Engineering
Volume 119, Issue 3
Abstract
The present paper illustrates the feasibility of using neural network models for priority assessment of highway pavement maintenance needs. Since neural networks are developed to mimic the decision‐making process of human beings and do not require users to predefine a mathematical equation relating pavement conditions to priority ratings, they offer an attractive means by which the priority setting process by highway maintenance personnel can be simulated. In the present study, the ability of a simple back‐propagation neural network was tested separately with three different priority‐setting schemes, using a general‐purpose microcomputer‐based neural network software. The priority‐setting schemes include a linear function relating priority ratings to pavement conditions, a nonlinear function, and subjective priority assessments obtained from a pavement engineer. For the first two schemes, noise was also introduced to examine how it would affect the performance of the neural network. Test results are positive and indicative of the potential of neural networks as a useful tool that highway agencies can use for priority rating in maintenance planning at the network level.
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References
1.
Biles, S., and Kerbel, R. (1979). “A training manual for setting street maintenance priorities.” TIG Tech. Transfer Rep. No. 2, Texas Innovation Group, Texas A&M University, College Station, Tex.
2.
Carmichael, R. F. III, Hudson, W. R., and Bishop, H. S. (1985). “Implementing pavement management in the Rhode Island.” N. Am. Pavement Mgmt. Conf., Vol. 2, Ontario Ministry of Transportation and Communications, Downsview, Ontario, Canada, 8.18–8.29.
3.
Chong, S. M. (1989). “A study of pavement maintenance and repair activities.” Project Rep., Dept. of Civil Engineering, National University of Singapore, Singapore.
4.
Dayhoff, J. E. (1990). Neural network architecture. Van Nostrand Reinhold, Princeton, N.J.
5.
Fwa, T. F., Sinha, K. C., and Riverson, J. D. N. (1988). “Highway routine maintenance programming at network level.” J. Transp. Engrg., ASCE, 114(5), 539–554.
6.
Fwa, T. F., Sinha, K. C., and Riverson, J. D. N. (1989). “Priority rating of highway routine maintenance activities.” Transp. Res. Rec. No. 1246, Transportation Research Board, Washington, D.C., 54–64.
7.
Hecht‐Nielsen, R. (1990). Neuraocomputing. Addison‐Wesley Publishing Co., Reading, Mass.
8.
Kikukawa, S., and Anzaki, Y. (1987). “Present situation and prospect of pavement maintenance management system in Japan.” Proc. 2nd No. Am. Conf. Managing Pavements, Vol. 1, Ontario Ministry of Transportation, Downsview, Ontario, Canada, 1.403–1.414.
9.
Jones, W. J., and Hoskins, J. (1987). “Back‐propagation, a generalized delta learning rule.” Byte Magazine, (Oct.), 10–15.
10.
Mercier, C. R. (1986). “Sufficiency ratings for secondary roads: model development.” Transp. Res. Rec. No. 1076, Transportation Research Board, Washington, D.C.,7–12.
11.
NeuralWorks User's Guide. (1988). Revision 2, NeuralWare, Inc., Sewickley, Pa.
12.
Rumelhart, D. E., and McClelland, J. L. (1986). Parallel distributed processing: Explorations in the microstructure of recognition. Vol. 1, MIT Press, Cambridge, Mass.
13.
Schoenberger, G. (1984). “A pavement management information system for evaluating pavements and setting priorities for maintenance.” Transp. Res. Rec. No. 951, Transportation Research Board, Washington, D.C., 60–63.
14.
Snaith, M. S., and Burrow, J. C. (1984). “Priority assessment.” Transp. Res. Rec. No. 951, Transportation Research Board, Washington, D.C., 9–13.
15.
Theberge, P. E. (1987). “Development of mathematical models to assess highway maintenance needs and establish rehabilitation threshold levels.” Transp. Res. Rec. No. 1109, Transportation Research Board, Washington, D.C., 27–35.
16.
Uzarski, D. R. (1984). “Managing better with PAVER.” Transp. Res. Rec. No. 951, 41–51.
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Copyright © 1993 American Society of Civil Engineers.
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Received: Oct 14, 1991
Published online: May 1, 1993
Published in print: May 1993
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