Estimating bridge performance based on a matrix-driven fuzzy linear regression model

Automation in Construction

Volumn 18, Issue 5, 2009, Pages 578-586

  Pan, Nang Fei ^a   Lin, Tzu Chieh ^a   Pan, Nai Hsin ^b  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^b NATIONAL YUNLIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Bridge inspection; Bridge performance; Deterioration prediction; Fuzzy regression analysis; Maintenance decision making

Indexed keywords

BRIDGE INSPECTION; BRIDGE PERFORMANCE; DETERIORATION PREDICTION; FUZZY REGRESSION ANALYSIS; MAINTENANCE DECISION-MAKING;

BRIDGE DECKS; COMPUTATIONAL LINGUISTICS; DETERIORATION; FUZZY SETS; INSPECTION; LINEAR REGRESSION; LINGUISTICS; MAINTENANCE; MATRIX ALGEBRA; VISUAL COMMUNICATION;

DECISION MAKING;

EID: 67349118138     PISSN: 09265805     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.autcon.2008.12.005     Document Type: Article

References (38)

1. The American Society for Civil Engineers, Report card for America's infrastructure, 2008, available at http://www.asce.org/reportcard/2005/actionplan07.cfm, accessed 11/27/2008.
2. Chassiakos A.P., Vagitotas P., and Theodorakopoulos D.D. A knowledge-based system for maintenance planning of highway concrete bridges. Advances in Engineering Software 36 (2005) 740-749
3. Cheng Y.-M., and Leu S.-S. Constrain-based clustering model for determining contract packages of bridge maintenance inspection. Automation in Construction 17 (2008) 682-690
4. Yehia S., Abudayyeh O., Fazal I., and Randolph D. A decision support system for concrete bridge deck maintenance. Advances in Engineering Software 39 (2008) 202-210
5. Heam G., Purvis R.L., Thompson P.D., Bushman W.H., McGhee K.K., and McKeel W.T. Bridge maintenance and management: a look to the future. Proceedings of the TRB 81 st Annual Meeting: A3C06: Structures Maintenance and management (2000) 1-7
6. Ugwu O.O., Kumaraswamy M.M., Kung F., and Ng S.T. Object-oriented framework for durability assessment and life cycle costing of highway bridges. Automation in Construction 14 (2005) 611-632
7. McCrea A., Chamberlain D., and Navon R. Automated inspection and restoration of steel bridges-a critical review of methods and enabling technologies. Automation in Construction 11 (2002) 351-373
8. Frangopol D.M., Kong J.S., and Gharaibeh E.S. Reliability-based life-cycle management of highway ridge. Journal of Computing in Civil Engineering, ASCE 15 1 (2001) 147-157
9. Lorenc S.J., Handlon B.E., and Bernold L.E. Development of a robotic bridge maintenance system. Automation in Construction 9 (2000) 251-258
10. Morcous G., Lounis Z., and Mirza S.M. Identification of environmental categories for Markovian deterioration models of bridge decks. Journal of Bridge Engineering, ASCE 8 6 (2003) 353-361
11. Scherer W.T., and Glagola D.M. Markov models for bridge maintenance management. Journal of Transportation Engineering, ASCE 120 1 (1994) 37-51
12. Jiang Y., Saito M., and Sinha K.C. Bridge performance prediction model using the Markov Chain. Transportation Research Record 1180 (1988) 25-32
13. Madanant S.M., and Wan W.H. Ibrahim, Poisson and negative binomial regression models for the computation of infrastructure transition probabilities. Journal of Transportation Engineering, ASCE 121 3 (1995) 267-272
14. Yen J., and Langari R. Fuzzy Logic: Intelligence, Control, and Information (1999), Prentice Hall, New Jersey, USA
15. Lee J., Sanmugarasa K., Blumestein M., and Loo Y.-C. Improving the reliability of a bridge management system (BMS) using an ANN-based backward prediction model (BPM). Automation in Construction 17 (2008) 758-722
16. Huang Y.H., Adams T.M., and Pincheira J.A. Analysis of life-cycle maintenance strategies for concrete bridge decks. Journal of Bridge Engineering, ASCE 9 3 (2004) 250-258
17. Cattan J., and Mohammadi J. Analysis of bridge condition rating data using neural networks. Microcomputers in Civil Engineering 12 (1997) 419-429
18. Morcous G., and Lounis Z. Maintenance optimization of infrastructure networks using genetic algorithms. Automation in Construction 14 (2005) 129-142
19. Miyamoto A., Kawamura K., and Makamura H. Bridge management system and maintenance optimization for existing bridges. Computer-Aided Civil and Infrastructure Engineering 15 (2000) 45-55
20. Furuta H., and He J.H. A fuzzy expert system for damage assessment using generic algorithm and neural networks. Microcomputing in Civil Engineering 11 (1996) 37-54
21. Pan N.-F. Performance prediction of highway bridges using fuzzy regression model. Proceedings of the Tenth International Conference on Civil, Structural and Environmental Engineering Computing (2005), Civil-Comp Press, Edinburgh, UK 1-15 Paper 9
22. Liang M.-T., Chu T.-B., Tsao W.-H., and Yeh C.-J. Determining the repair ranking of existing RC bridges using fuzzy synthetic evaluation method. Journal of Chinese Institute of Engineers, 29 1 (2006) 37-50
23. Sasmal S., Ramanjaneyulu K., Gopalakrishnan S., and Lakshmanan N. Fuzzy logic based bondition rating of existing reinforced concrete bridges. Journal of Performance of Constructed Facilities, ASCE 20 3 (2006) 261-273
24. Tanaka H., Uejima S., and Asai K. Linear regression analysis with fuzzy model. IEEE Transactions on System, Man and Cybernet 2 6 (1982) 903-907
25. Savic D.A. Evaluation of fuzzy linear regression models. Fuzzy Sets and Systems 39 (1991) 51-63
26. Diamond P., and Korner R. Extended fuzzy linear models and least-squares estimates. Computers and Mathematics with Applications 33 (1997) 15-32
27. Kim B., and Bishu R.R. Evaluation of fuzzy linear regression models by comparing membership functions. Fuzzy Sets and Systems 110 (1998) 343-352
28. Chang Y.-H.O., and Ayyub B.M. Hybrid fuzzy regression analysis and its applications. Uncertainty Modelling and Analysis in Civil Engineering (1996), CRC Press, NY
29. D'Urso P. Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data. Computational Statistics and Data Analysis 42 (2003) 47-72
30. Chang P.-T., and Lee E.S. Fuzzy least absolute deviations regression and the conflicting trends in fuzzy parameters. Computers & Mathematics with Applications 28 5 (1994) 89-101
31. P.-T. Chang, Fuzzy regression analysis, Ph.D. Thesis, Industrial Engineering, Kansas State University, USA, 1994.
32. 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 (2005), Civil-Comp Press, Edinburgh, UK 1-14 Paper 3
33. Taiwan Area National Freeway Bureau, Visual inspection manual for freeway bridges (in Chinese), Taiwan Area National Freeway Bureau, 1995.
34. de Fleuriot E., Nordengen P.A., Lee Y.-F., and Lin A.-Y. A bridge management system for the Taiwan Area National Freeway Bureau. International Bridge Conference: Bridges into the 21st Century, Hong Kong (October 1995) 611-618
35. Neter J., Wasserman W., and Kutner M.H. Applied Regression Models. 2nd ed. (1996), IRWIN, Inc., NY
36. Taiwan Area National Freeway Bureau, 2007, Bridge Management System, available at http://bms.iot.gov.tw, accessed 01/15/2007.
37. Pan N.F. Applying Fuzzy Regression to Forecast Bridge Conditions, Technical Report (2008), the National Science Council, Taiwan
38. Lapin L. Modern Engineering Statistics (1997), Duxbury Press, NY