Forecasting bridge deck conditions using fuzzy regression analysis

Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an

Volumn 30, Issue 4, 2007, Pages 593-603

  Pan, Nang Fei ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Bridge concrete deck; Deterioration prediction; Fuzzy regression model; Ordinary regression analysis

Indexed keywords

DETERIORATION; FUZZY RULES; MATHEMATICAL MODELS; NUMERICAL METHODS; REGRESSION ANALYSIS;

BRIDGE CONCRETE DECK; DETERIORATION PREDICTION; FUZZY REGRESSION MODELS; ORDINARY REGRESSION ANALYSIS;

BRIDGE DECKS;

EID: 34547369755     PISSN: 02533839     EISSN: 21587299     Source Type: Journal    
DOI: 10.1080/02533839.2007.9671288     Document Type: Article

References (26)

1. Busa, G.D., 1985. “Modeling Concrete Bridge Deck Deterioration,”. MA, USA:Department of Civil Engineering, MIT. Master's Thesis
2. Chang, P.T., and Lee, E.S. 1996. “A Generalized Fuzzy Weighted Least-Squares Regression,”. Fuzzy sets and systems, 82:289–298.
3. Chang, Y. H, and Ayyub, B.M., 1996. “Hybrid Fuzzy Regression Analysis and Its Applications,”. In Uncertainty Modelling and Analysis in Civil Engineering, 33–41. NY, USA:CRC Press Inc.
4. Chiang, W., Liu, F.R., and Lee, J., 2000. “Bridge Damage Assessment Through Fuzzy Petri Net Based Expert System,”. Journal Computing in Civil Engineering, ASCE, 14(2):141–149.
5. CSIR. 1994. “TANFB Bridge Management System Description of Modules and Computer Options,”. South Africa:TANFB.
6. D'Urso, P., and Gastaldi, T., 2002. “An Orderwise Polynomial Regression Procedure for Fuzzy Data, ”. Fuzzy Sets and Systems, 130:1–19.
7. Frangopol, D.M., Kong, J.S., and Gharaibeh, E.S., 2001. “Reliability-Based Life-Cycle Management of Highway Bridge,”. Journal of Computing in Civil Engineering, ASCE, 15 (1):147–57.
8. Furuta, H., and He, J.H., 1996. “A Fuzzy Expert System for Damage Assessment using Generic Algorithm and Neural Networks,”. Microcomputing in Civil Engineering, 11:37–54.
9. Huang, Y.H, Adams, T.M, and Pincheira, J.A. 2004. “Analysis of Life-Cycle Maintenance Strategies for Concrete Bridge Decks,”. Journal of Bridge Engineering, ASCE, 9 (3):250–58.
10. Jiang, Y., Saito, M., and Sinha, K.C., 1988. “Bridge Performance Prediction Model using the Markov Chain,”. Transportation Research Record, 1180:25–32.
11. Lapin, L., 1997. Modern Engineering Statistics, NY, USA:Duxbury Press.
12. Madanant, S.M., Wan and Ibrahim, W. H., 1995. “Poisson and Negative Binomial Regression Models for the Computation of Infrastructure Transition Probabilities,”. Journal of Transportation Engineering, ASCE, 121 (3):267–72.
13. McElvey, R.D., and Zavoina, W., 1975. “A Statistical Model for the Analysis of Ordinary Level Dependent Variables,”. Journal of Mathematics Sociology, 4:103–20.
14. Madanant, S.M., Mishalani, R., Wan and Ibrahim, W. H., 1995. “Estimation of Infrastructure Transition Probabilities from Condition Rating Data,”. Journal of Infrastructure Systems, ASCE, 1 (2):120–25.
15. Newlon, H., Davis, J., and North, M., 1973. “Bridge Deck Performance in Virginia,”. Transportation Research Record, 423:58–72.
16. Pan, N.F., “Assessment of Causes of Building Collapse using Fuzzy Regression Analysis,”. Proceedings of the 4th International Conference on Engineering Computational Technology,. Edited by:Topping, B.H.V., pp. 1–13. Edinburgh, UK:Civil-Comp Press.
17. Rattanasuwan, P., 1998. “Estimating NBI Ratings using a Neural Network,”. Madison, WI, USA.:Department of Civil and Environmental Engineering, University of Wisconsin. Master's Thesis
18. Sasmal, S., Ramanjaneyulu, K., Gopalakrishnan, S., and Lakshmanan, N., 2006. “Fuzzy Logic Based Condition Rating of Existing Reinforced Concrete Bridges,”. Journal of Performance of Constructed Facilities, ASCE, 20(3):261–273.
19. Savic, D.A., 1991. “Evaluation of Fuzzy Linear Regression Models,”. Fuzzy Sets and Systems, 39:51–63.
20. Scherer, W.T., and Glagola, D.M., 1994. “Markov Models for Bridge Maintenance Management,”. Journal of Transportation Engineering, ASCE, 120 (1):37–51.
21. Sobanjo, J.O., “A Neural Network Approach to Modeling Bridge Deterioration,”. Computing in Civil Engineering, Proceedings of the Fourth Congress, ASCE. Philadelphia, PA, USA. pp. 623–626.
22. Taiwan Area National Freeway Bureau. 2004. “Bridge Management System,”. Taiwan:ROC. http://bms.iot.gov.tw
23. Tanaka, H., Uejima, S., and Asai, K., 1982. “Linear Regression Analysis with Fuzzy Model,”. IEEE Systems Transaction, Systems Man Cybernet,:903–07. SMC-2(6)
24. Yager, R.R., and Filev, D.P., 1982. “On the Issue of Defuzzification and Selection Based on a Fuzzy Set,”. Fuzzy Sets and Systems, 55 (3):255–72.
25. Yau, N.J., and Liao, H.K., “An Automated Visual-Aid System for Inspecting Concrete Bridges,”. Proceedings of the 10th International Conference on Civil, Structural and Environmental Engineering Computing,. Edited by:Topping, B.H.V., pp. 1–14. Edinburgh, UK:Civil-Comp Press.
26. Zhao, Z.Y., and Chen, C. Y., 2002. “A Fuzzy System for the Concrete Bridge Damage Diagnosis,”. Journal of Computers & Structures, 80(7–8):629–641.