Prediction of pavement performance through neuro-fuzzy reasoning

Computer-Aided Civil and Infrastructure Engineering

Volumn 25, Issue 1, 2010, Pages 39-54

  Bianchini, Alessandra ^a   Bandini, Paola ^a  

^a New Mexico State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FALLING WEIGHT DEFLECTOMETERS; FLEXIBLE PAVEMENTS; GENERALIZATION CAPABILITY; GOVERNMENT AGENCIES; HYBRID MODEL; LINEAR REGRESSION MODELS; MATHEMATICAL MODELING; MODEL PERFORMANCE; NEURO-FUZZY MODEL; NEURO-FUZZY REASONING; PAVEMENT CONDITION; PAVEMENT MANAGEMENT; PAVEMENT PERFORMANCE; PAVEMENT SURFACE; REASONING PROCESS;

FEEDFORWARD NEURAL NETWORKS; FUZZY NEURAL NETWORKS; LINEAR REGRESSION; MATHEMATICAL TECHNIQUES; MULTILAYER NEURAL NETWORKS;

PAVEMENTS;

ARTIFICIAL INTELLIGENCE; FUZZY MATHEMATICS; NUMERICAL MODEL; PAVEMENT;

EID: 72549118772     PISSN: 10939687     EISSN: 14678667     Source Type: Journal    
DOI: 10.1111/j.1467-8667.2009.00615.x     Document Type: Article

References (68)

1. AASHTO Guide for Design of Pavement Structures 1993, AASHTO (American Association of State Highway and Transportation Officials), The Association, Washington, DC
2. Adeli H, Hung S L. A fuzzy neural network learning model for image recognition. Integrated Computer-Aided Engineering 1993a, 1(1):43-55.
3. Adeli H, Hung S L. A concurrent adaptive conjugate gradient learning algorithm on MIMD machines. Journal of Supercomputer Applications 1993b, 7(2):155-66. MIT Press
4. Adeli H, Hung S L. An adaptive conjugate gradient learning algorithm for effective training of multilayer neural networks. Applied Mathematics and Computation 1994, 62(1):81-102.
5. Adeli H, Jiang X. Neuro-fuzzy logic model for freeway work zone capacity estimation. Journal of Transportation Engineering 2003, 129(5):484-93.
6. Adeli H, Jiang X. Dynamic fuzzy wavelet neural network model for structural system identification. Journal of Structural Engineering 2006, 132(1):102-11.
7. Adeli H, Karim A. Fuzzy-Wavelet RBFNN model for freeway incident detection. Journal of Transportation Engineering 2000, 126(6):464-71.
8. Adeli H, Park H S. Counter propagation neural network in structural engineering. Journal of Structural Engineering 1995, 121(8):1205-12.
9. Balasko B, Abonyi J, Feil B. Fuzzy Clustering and Data Analysis Toolbox 2002, http://www.fmt.vein.hu/softcomp/fclusttoolbox/, Department of Process Engineering, University of Veszprem, Hungary, Retrieved February 15, 2007, from
10. Bianchini A. Prediction of pavement performance through neuro-fuzzy reasoning. 2007, Ph.D. dissertation, New Mexico State University, Las Cruces
11. Butt A A, Shahin M Y, Feighan K J, Carpenter H C. Pavement performance prediction using the Markov process. Transportation Research Record 1123 1992, 12-19. TRB, National Research Council, Washington, DC, pp
12. Cammarata S. Reti Neuronali-Dal Perceptron alle Reti Caotiche e Neuro-Fuzzy 1997, 2, nd edn., EtasLibri, Milan
13. Carden E P, Brownjohn J M W. Fuzzy clustering of stability diagrams for vibration-based structural health monitoring. Computer-Aided Civil and Infrastructure Engineering 2008, 23(5):360-72.
14. Carey W, Irick P. The pavement serviceability performance concept. 1960
15. Carey W, Irick P. The Pavement Serviceability Performance Concept 1962, Highway Research Board Special Report 61E, AASHO Road Test
16. Chadbourn B. Reliability, Damage, and Seasonal Considerations in the Mnpave Mechanistic-Empirical Asphalt Pavement Design Computer Program 2001, Office of Materials, Minnesota Department of Transportation, Saint Paul, MN
17. Chao L C. Fuzzy logic model for determining minimum bid markup. Computer-Aided Civil and Infrastructure Engineering 2007, 22(6):449-60.
18. Choi J, Adams T M, Bahia H U. Pavement roughness modeling using back-propagation neural networks. Computer-Aided Civil and Infrastructure Engineering 2004, 19(4):295-303.
19. Delatte N J, Safarjalani M, Zinger N B. Concrete Pavement Performance in the Southeastern United States 2000, University Transportation Center for Alabama, Tuscaloosa, AL
20. Dharia A, Adeli H. Neural network model for rapid forecasting of freeway link travel time. Engineering Applications of Artificial Intelligence 2003, 16(7-8):607-13.
21. Eldin N N, Senouci A B. A pavement condition-rating model using backpropagation neural networks. Microcomputers in Civil Engineering 1995, 10(6):433-41.
22. Distress Identification Manual for the Long-Term Pavement Performance Program 2003, FHWA (U.S. Federal Highway Administration), Publication No. FHWA-RD-03-031, Washington, DC
23. Funahashi K. On the approximate realization of continuous mapping by neural networks. Neural Networks 1989, 2(3):183-92.
24. Garg N, Thompson M R. Structural response of LVR flexible pavements at MN/road project. Journal of Transportation Engineering 1999, 125(3):238-44.
25. Hall K T, Muñoz C E. Estimation of present serviceability index from international roughness index. Transportation Research Record 1655 1999, 93-9. TRB, National Research Council, Washington, DC, pp
26. Haykin S. Neural Networks-A Comprehensive Foundation 1999, 2nd edn., Prentice-Hall, Upper Saddle River, NJ
27. Hong H P, Wang S S. Stochastic modeling of pavement performance. International Journal of Pavement Engineering 2003, 4(4):235-43.
28. Hornik K, Stinchcombe M, White H. Multilayer feedforward networks are universal approximators. Neural Networks 1989, 5(5):78-93.
29. Hung S L, Adeli H. Parallel backpropagation learning algorithms on Cray Y-MP8/864 Supercomputer. Neurocomputing 1993, 5(6):287-302.
30. Jiang X, Adeli H. Fuzzy clustering approach for accurate embedding dimension identification in chaotic time series. Integrated Computer-Aided Engineering 2003, 10(3):287-302.
31. Jiang X, Adeli H. Dynamic wavelet neural network model for traffic flow forecasting. Journal of Transportation Engineering 2005, 131(10):771-79.
32. Jiang X, Adeli H. Dynamic fuzzy wavelet neuroemulator for nonlinear control of irregular highrise building structures. International Journal for Numerical Methods in Engineering 2008, 74(7):1045-66.
33. Jin X L, Doloi H. Modelling risk allocation decision-making in PPP projects using fuzzy logic. Computer-Aided Civil and Infrastructure Engineering 2009, 24(7).
34. Karim A, Adeli H. Comparison of the fuzzy-wavelet RBFNN freeway incident detection model with the California algorithm. Journal of Transportation Engineering 2002, 128(1):21-30.
35. Kasabov N. Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering 1998, MIT Press, Cambridge, MA
36. Klir G J, Yuan B. Fuzzy Sets and Fuzzy Logic: Theory and Applications 1995, Prentice-Hall, Upper Saddle River, NJ
37. Li N, Xie W C, Haas R. Reliability-based processing of Markov chains for modeling pavement network deterioration. Transportation Research Record 1524 1996, 203-13. TRB, National Research Council, Washington, DC, pp
38. Loizos A, Karlaftis A. Investigating pavement cracking: an evolutionary modular neural network approach. Transportation Research Record 1970 2006, 207-14. TRB, National Research Council, Washington, DC, pp
39. Mantegna R N, Stanley H E. An Introduction to Econophysics: Correlation and Complexity in Finance 1999, Cambridge University Press, Cambridge, MA
40. Statistics Toolbox 6 User's Guide 2007, MathWorks, Inc, Natick, MA
41. Mei X, Gunaratne M, Lu J J, Dietrich B. Neural network for rapid depth evaluation of shallow cracks on asphalt pavements. Computer-Aided Civil and Infrastructure Engineering 2004, 19(3):223-30.
42. Nauck D, Klawonn F, Kruse R. Foundations of Neuro-Fuzzy Systems 1997, Wiley, NY
43. Nomura Y, Furuta H, Hiorkane M. An integrated fuzzy control system for structural vibrations. Computer-Aided Civil and Infrastructure Engineering 2007, 22(4):306-16.
44. Ovik J M, Birgisson B, Newcomb D. Characterizing Seasonal Variations in Pavement Material Properties for Use in a Mechanistic-Empirical Design Procedure 2000, Minnesota Department of Transportation, Report No. MN/RC-2000-35, Saint Paul, MN
45. Palmquist D, Worel B, Zerfas W. 2002 Mn/Road Hot-Mix Asphalt Mainline Test Cell Condition Report 2002, Minnesota Department of Transportation, Saint Paul, MN
46. Park H M, Kim Y R. Prediction of remaining life of asphalt pavement with falling-weight deflectometer multiload-level deflections. Transportation Research Record 1860 2003, 48-56. TRB, National Research Council, Washington, DC, pp
47. Park H S, Adeli H. A neural dynamics model for structural optimization-application to plastic design of structures. Computers and Structures 1995, 57(3):391-99.
48. Poggio T, Girosi F. Networks for approximation and learning. Proceedings of the Institute of Electrical and Electronics Engineers 1990, 78(9):1481-97.
49. Provenzano P. A fuzzy neural network method for modeling uncertainties in soil-structure interaction problem. Computer-Aided Civil and Infrastructure Engineering 2003, 18(6):391-411.
50. Prozzi J A, Madanat S M. Incremental nonlinear model for predicting pavement serviceability. Journal of Transportation Engineering 2003, 129(6):635-41.
51. Ross T J. Fuzzy Logic with Engineering Application 2004, Wiley, NY
52. Saltan M, Tigdemir M, Karasahin M. Artificial neural network application for flexible pavement thickness modeling. Turkish Journal of Engineering and Environmental Science 2002, 26:246-48.
53. Samant A, Adeli H. Enhancing neural network incident detection algorithms using wavelets. Computer-Aided Civil and Infrastructure Engineering 2001, 16(4):239-45.
54. Sarma K, Adeli H. Fuzzy genetic algorithm for optimization of steel structures. Journal of Structural Engineering 2000a, 126(5):596-604.
55. Sarma K, Adeli H. Fuzzy discrete multicriteria cost optimization of steel structures. Journal of Structural Engineering 2000b, 126(11):1339-47.
56. Sayers M W, Karamihas S M. The Little Book of Profiling 1998, The Regent of the University of Michigan, Ann Arbor, MI
57. Shahin M Y. Pavement Management for Airports, Roads and Parking Lots 1994, Chapman and Hall, NY
58. Sirca G, Adeli H. Neural network model for uplift load capacity of metal roof panels. Journal of Structural Engineering 2001, 127(11):1276-85.
59. Stathopoulos A, Dimitriou L, Tsekeris T. Fuzzy modeling approach for combined forecasting of urban traffic flow. Computer-Aided Civil and Infrastructure Engineering 2008, 23(7):521-35.
60. Stehr R H. Guidelines for seasonal load limit starting and ending dates. 2004, Engineering Services Division, Minnesota Department of Transportation, Saint Paul, MN
61. Takagi H, Hayashi I. NN-driven fuzzy reasoning. International Journal of Approximate Reasoning 1991, 5(3):191-212.
62. Uzan J, Lytton R L. Structural design of flexible pavements: a simple predictive system. Transportation Research Record 888 1982, 61-72. TRB, National Research Council, Washington, DC, pp
63. Van Gurp C A P M, Cortnraad W M H, Houtman F, Von Quintas H L, Bush A J, Baladi G Y. Development of analytical/empirical performance parameters for the structural evaluation of asphalt pavements. Nondestructive Testing of Pavements and Backcalculation of Moduli 1989, Vol. 2:589-98. in, eds., ASTM STP 1026, American Society of Testing and Materials, Philadelphia, PA, pp
64. Vennalaganti K M, Ferregut C, Nazarian S, Von Quintas H L, Bush A J, Baladi G Y. Stochastic analysis of errors in remaining life due to misestimation of pavement parameters in NDT. Nondestructive Testing of Pavements and Backcalculation of Moduli 1994, Vol. 2:478-95. in, eds., ASTM STP 1198, American Society of Testing and Materials, Philadelphia, PA, pp
65. Xu B, Ranjithan S R, Kim Y R. New relationships between falling weight deflectometer deflections and asphalt pavement layer condition indicators. Transportation Research Record 1806 2002a, 48-56. TRB, National Research Council, Washington, DC, pp
66. Xu B, Ranjithan S R, Kim Y R. New condition assessment procedure for asphalt pavement layers using falling weight deflectometer deflections. Transportation Research Record 1806 2002b, 57-69. TRB, National Research Council, Washington, DC, pp
67. Yang J, Lu J J, Gunaratne M, Dietrich B. Modeling crack deterioration of flexible pavements: comparison of recurrent Markov chains and artificial neural networks. Transportation Research Record 1974 2006, 18-25. TRB, National Research Council, Washington, DC, pp
68. Zhang Z, Claros G, Manuel L, Damnjanovic I. Development of structural condition index to support pavement maintenance and rehabilitation decisions at network level. Transportation Research Record 1827 2003, 10-17. TRB, National Research Council, pp, Washington, DC