Finite element based adaptive neuro-fuzzy inference technique for parameter identification of multi-layered Transportation structures

Transport

Volumn 25, Issue 1, 2010, Pages 58-65

  Gopalakrishnan, Kasthurirangan ^a   Khaitan, Siddhartha Kumar ^a  

^a Iowa State University of Science and Technology   (United States)

Author keywords

Finite element; Fuzzy inference; Neural networks; Non destructive testing; Pavement; Transportation structures

Indexed keywords

BRIDGE DECKS; DYNAMIC LOADS; ELASTIC MODULI; FINITE ELEMENT METHOD; FUZZY NEURAL NETWORKS; INVERSE PROBLEMS; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; PAVEMENTS; STRUCTURAL ANALYSIS; TRANSPORTATION;

ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM; ADAPTIVE NEURO-FUZZY INFERENCE; FALLING WEIGHT DEFLECTOMETER (FWD); FLEXIBLE PAVEMENT STRUCTURE; NON DESTRUCTIVE TESTING; STRUCTURAL ANALYSIS AND DESIGNS; TRANSPORTATION AGENCIES; TRANSPORTATION STRUCTURES;

FUZZY INFERENCE;

EID: 77950496713     PISSN: 16484142     EISSN: 16483480     Source Type: Journal    
DOI: 10.3846/transport.2010.08     Document Type: Article

References (21)

1. Abolpour, B.; Javan, M.; Karamouz, M. 2007. Water allocation improvement in river basin using adaptive neural fuzzy reinforcement learning approach, Applied Soft Computing 7(1): 265-285. doi:10.1016/j.asoc.2005.02.007 (Pubitemid 44739432)
2. Ceylan, H.; Guclu, A.; Bayrak, M. B.; Gopalakrishnan, K. 2007. Nondestructive Evaluation of Iowa Pavements: Phase I. Final Report. CTRE Project 04-177. Center for Transportation Research and Education (CTRE), Iowa State University, Ames, IA. 136 p. Available from Internet: 〈www.intrans.iastate. edu/reports/nde-pavements.pdf〉.
3. Colorni, A.; Dorigo, M.; Maffioli, F.; Maniezzo, V.; Righini, G.; Trubian, M. 1996. Heuristics from nature for hard combinatorial optimization problems, International Transactions in Operations Research 3(1): 1-21. doi:10.1111/j.1475-3995.1996.tb00032.x (Pubitemid 126122665)
4. Use of Nondestructive Testing in the Evaluation of Airport Pavements. 2004. U.S. Department of Transportation, Federal Aviation Administration (FAA). FAA Advisory Circular No. 150/5370-11A. Available from Internet: 〈http://purl.access.gpo.gov/GPO/LPS111166〉.
5. Garg, N. 2002. Post-Traffic Activities Conducted in CC1 Flexible Pavements: November 2001 - March 2002. Presented at the FAA Airport Pavement Working Group Meeting, Atlantic City, NJ.
6. Göktepe, A. B.; Aǧar, E.; Lav, A. H. 2004. Comparison of multilayer perceptron and adaptive neuro-fuzzy system on backcalculating the mechanical properties of flexible pavements, ARI - The Bulletin of the Istanbul Technical University 54(3): 65-77. Available from Internet: 〈www.ari.itu. edu.tr/pre-art4/lav.pdf〉. (Pubitemid 44254266)
7. Hoffman, M. S.; Thompson, M. R. 1982. Backcalculating nonlinear resilient moduli from deflection data, Transportation Research Record: Journal of the Transportation Research Board 852: 42-51.
8. Irwin, L. H.; Szenbenyi, T. 1991. User's Guide to MODCOMP3 Version 3.2. CLRP Report No 91-4, Cornell University, Local Roads Program, Ithaca, NY.
9. Irwin, L. H. 1994. Instructional Guide for Back-Calculation and the Use of MODCOMP. CLRP Publication No 94-10, Cornell University, Local Roads Program, Ithaca, NY.
10. Jang, J.-S. R. 1993. ANFIS - Adaptive-Network-Based Fuzzy Inference Systems, IEEE Transactions on Systems Man andCybernetics 23(3): 665-685. doi:10.1109/21.256541
11. Jang, J.-S. R; Sun, C.-T.; Mizutani, E. 1997. Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Prentice-Hall. 614 p.
12. Mamdani, E. H.; Assilian, S. 1975. An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies 7(1): 1-13. doi:10.1016/S0020-7373(75)80002-2
13. Meier, R. W.; Rix, G. J. 1995. Backcalculation of flexible pavement moduli from dynamic deflection basins using artificial neural networks, Transportation Research Record: Journal of the Transportation Research Board 1473: 72-81.
14. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures. 2004. National Cooperative Highway Research Program (NCHRP). NCHRP 1-37A, Final Report
15. Oh, S.-K.; Pedrycz, W.; Ahn, T.-C. 2002. Self-organizing neural networks with fuzzy polynomial neurons, Applied Soft Computing 2(1): 1-10. doi:10.1016/S1568-4946(02)00023-6 (Pubitemid 40442470)
16. Layer Moduli Backcalculation Procedure: Software Selection. 1993. Final Report. SHRP-P651. Strategic Highway Research Program (SHRP), National Academy of Sciences, Washington, D.C. Available from Internet: 〈http://on-linepubs. trb.org/onlinepubs/shrp/SHRP-P-651.pdf〉.
17. Raad, L.; Figueroa, J. L. 1980. Load response of transportation support systems, Transportation Engineering Journal of ASCE 106(1): 111-128. (Pubitemid 10421322)
18. Saltan, M.; Saltan, S.; Sahiner, A. 2007. Fuzzy logic modeling of deflection behavior against dynamic loading in flexible pavements, Construction and Building Materials 21(7): 1406-1414. doi:10.1016/j.conbuildmat.2006.07.004 (Pubitemid 46367594)
19. Takagi, T.; Sugeno, M. 1985. Fuzzy identification of systems and its applications, IEEE Transactions on Systems Man and Cybernetics 15(1): 116-132.
20. Van Cauwelaert, F. J.; Alexander, D. R.; White, T. D.; Barker, W. R. 1989. Multilayer elastic program for backcalculating layer moduli in pavement evaluation, in Nondestructive Testing of Pavements and Backcalculation of Moduli, ASTM STP 1026, A. J. Bush III and G.Y. Baladi, Eds., American Society for Testing and Materials, Philadelphia, 171-188.
21. Zadeh, L. A. 1965. Fuzzy sets, Information and Control 8(3): 338-353. doi:10.1016/S0019-9958(65)90241-X