Group method of data handling to predict scour depth around vertical piles under regular waves

Scientia Iranica

Volumn 20, Issue 3, 2013, Pages 406-413

  Najafzadeh, M ^a   Barani, G A ^a   Hessami Kermani, M R ^a  

^a SHAHID BAHONAR UNIVERSITY OF KERMAN   (Iran)

Author keywords

Group method of data handling; Levenberg Marquardt; Scour depth; Vertical pile; Wave

Indexed keywords

BRIDGE PIERS; DATA HANDLING; EXPERIMENTAL REACTORS; FORECASTING; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; REYNOLDS NUMBER; SCOUR; SENSITIVITY ANALYSIS; WAVES;

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; GROUP METHOD OF DATA HANDLING; KEULEGAN-CARPENTER NUMBER; LEVENBERG-MARQUARDT; LEVENBERG-MARQUARDT METHOD; RADIAL BASIS FUNCTION NEURAL NETWORKS; SCOUR DEPTH; VERTICAL PILES;

PILES;

ARTIFICIAL NEURAL NETWORK; EMPIRICAL ANALYSIS; FUZZY MATHEMATICS; NUMERICAL MODEL; PREDICTION; REYNOLDS NUMBER; SCOUR; WAVE;

EID: 84888325821     PISSN: 10263098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.scient.2013.04.005     Document Type: Article

References (43)

1. Dey, S., Sumer, M. and Fredsoe, J. Control of scour at vertical circular piles under waves and current, J. Hydraul. Eng., 132(3), pp. 270-279 (2006).
2. Breusers, H.N.C., Nicollet, G. and Shen, H.W. Local scour around cylindrical piers, J. Hydraul. Res., 153, pp. 211-252 (1977).
3. Chiew, Y.M. Local scour at vertical piles under wave action, In Proc., 9th Australian Conf. on Coastal and Ocean Eng., pp. 393-396, Ade-laide, Australia (1989).
4. Dey, S. Local scour at piers. Part II: bibliography, Int. J. Sediment. Res., 122, pp. 47-57 (1997).
5. Palmer, H.D. Wave-induced scour on the sea floor, Proc. Civ. Eng. in the Oceans II, ASCE (Dec), pp. 703-7169 (1969).
6. Das, M.M., A literature review on bed-load transport due to wave action and localized scour in non-cohesive sediments, Final Report HEL 21-6: A Literature Review on Erosion and Deposition of Sediment near Structures in the Ocean (1970).
7. R -K, Wang and Herbich, J.B., Combined current and wave produced scour around a single pile, CEO Rep. 269, Texas Eng. Experiment Station, Dept. Civ. Eng. Texas University System (1983).
8. Herbich, J.B., Schiller Jr., R.E., Watanabe, R.K. and Dunlap, W.A., Seafloor Scour. Design Guidelines for Ocean-Founded Structures, Marcell Dekker, New York (1984).
9. Eadie, R.W. IV. and Herbich, J.B. Scour about a single, cylindrical pile due to combined random waves and current, Proc., 20th. Coast. Eng.Conf., 3, pp. 1858-1870 (1986).
10. Sumer, B.M., Fredsoe, J. and Christiansen, N. Scour around a vertical pile in waves, J. Waterway. Port. Coast. Ocean Eng., 118(1), pp. 15-31 (1992).
11. Sumer, B.M., Christiansen, N. and Fredsoe, J. Influence of cross section on wave scour around piles, J. Waterway. Port. Coast. Ocean Eng., 119(5), pp. 477-495 (1994).
12. Sumer, B.M. and Fredsoe, J. Scour around pile in combined waves and current, J. Hydraul. Eng., 127(5), pp. 403-411 (2001).
13. Bateni, S.M., Borghei, S.M. and Jeng, D.S. Neural network and neuro-fuzzy assessments for scour depth around bridge piers, Eng. Appl. Artif. Intell., 20, pp. 401-414 (2007).
14. Ayoubloo, M.K., Etemad-Shahidi, A. and Mahjoobi, J. Evaluation of regular wave scour around a circular pile using data mining approaches, Appl. Ocean. Res., 32(1), pp. 34-39 (2010).
15. Guven, A. and Gunal, M. Genetic programming approach for prediction of local scour downstream of hydraulic structures, J. Irrig. Drain. Eng., 134(2), pp. 241-249 (2008).
16. Guven, A., Azamathulla, H.Md. and Zakaria, N. Linear genetic programming for prediction of circular piles scour, Ocean Eng., 36, pp. 985-991 (2009).
17. Azamathulla, H.Md., Guven, A. and Demir, Y.K. Linear genetic programming to scour below submerged pipeline, Ocean Eng., 38(8-9), pp. 995-1000 (2011).
18. Najafzadeh, M. and Barani, G.A. Comparison of group method of data hadling based genetic programminig and back propagation systems to predict scour depth around Bridge Pier, Sci. Iran. Trans. A. Civ. Eng., 18(6), pp. 1207-1213 (2011).
19. Najafzadeh, M. and Azamathulla, H.M. Group method of data handling to predict scour depth around bridge piers, Neural Comput. Appl., (2012), http://dx.doi.org/10.1007/s00521-012-1160-6.
20. Najafzadeh, M., Barani, G.A. and Hessami Kermani, M.R. Aboutment scour in live-bed and clear-water using GMDH network, Water Sci. Technol., 67(5), pp. 1121-1128 (2013).
21. Najafzadeh, M., Barani, G.A. and Azamathulla, H.Md. GMDH to prediction of scour depth around vertical piers in cohesive soils, Appl. Ocean Res., 40, pp. 35-41 (2013).
22. Najafzadeh, M., Barani, G.A. and Hessami Kermani, M.R. GMDH network based back propagation algorithm to predict abutment scour in cohesive soils, Ocean Eng., 59, pp. 100-106 (2013).
23. Najafzadeh, M., Barani, G.A. and Azamathulla, H.M. Prediction of pipeline scour depth in clear-water and live-bed conditions using group method of data handling, Neural Comput. Appl., (2012), http://dx.doi.org/10.1007/s00521-012- 1258-x.
24. Najafzadeh, M. and Barani, G.A. Discussion of Genetic Programming to Predict River Pipeline Scour by H. Md. Azamathulla and A. Ab. Ghani, J. Pipeline Syst. Eng. Pract., (2013), http://dx.doi.org/10.1061/(ASCE)PS.1949- 1204.0000146.
25. Amanifard, N., Nariman-Zadeh, N., Farahani, M.H. and Khalkhali, A. Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks, J. Energy. Conver. Manag., 49(8), pp. 2588-2594 (2008).
26. Witczak, M., Korbicz, J., Mrugalski, M. and Patton, R. A GMDH neural network-based approach to robust fault diagnosis: Application to the DAMADICS benchmark problem, J. Control. Eng. Pract., 14(6), pp. 671-683 (2006).
27. Mehrara, M., Moeini, A., Ahrari, M. and Erfanifard, A. Investigating the efficiency in oil futures market based on GMDH approach, Expert. Syst. Appl., 36(4), pp. 7479-7483 (2009).
28. Sumer, B.M., Hatipoglu, F. and Fredsoe, J. Wave scour around a pile in sand, medium dense and dense silt, J. Waterway. Port. Coast. Ocean Eng., 133(1), pp. 14-27 (2007).
29. Madala, H.R. and Ivakhnenko, A.G., Inductive Learning Algorithms for Complex Systems Modeling, CRC Press, Boca Raton, FL (1994).
30. Ivahnenko, A.G. Polynomial theory of complex systems, IEEE Trans. Syst. Man. Cybern, (1971).
31. Iba, H. and de Garis, H. Extending genetic programming with recombinative guidance, In Advances in Genetic Programming, 2, P. Angeline and K. Kinnear, Eds., MIT Press, Cambridge (1996).
32. Onwubolu, G.C. Design of hybrid differential evolution and group method in data handling networks for modeling and prediction, Inf. Sci., 178, pp. 3618-3634 (2008).
33. Sakaguchi, A. and Yamamoto, T. AGMDHnetwork using back propagation and its application to a controller design, J. IEEE., 4, pp. 2691-2697 (2000).
34. Srinivasan, D. Energy demand prediction using GMDH networks, Neuro- Computing, 72(1-3), pp. 625-629 (2008).
35. Farlow, S.J., Ed., Self-Organizing Method in Modelling: GMDH Type Algorithm, Marcel Dekker Inc. (1984).
36. Sanchez, E., Shibata, T. and Zadeh, L.A., Genetic Algorithms and Fuzzy Logic Systems, World Scienctific (1997).
37. Levenberg, K.A. Method for the solution of certain non-linear problems in least squares, Q. Appl. Math., 2(2), pp. 164-168 (1944).
38. Marquardt, D.W. An algorithm for the least-squares estimation of nonlinear parameters, SIAM J. Appl. Math., 11(2), pp. 431-441 (1963).
39. Jacoby, S.L.S., Kowalik, J.S. and Pizzo, J.T., Iterative Methods for Nonlinear Optimization Problems, Prentice-hall, Inc., Englewood Cliffs, NJ (1972).
40. Jang, J.S.R. ANFIS: adaptive-network-based fuzzy inference system, IEEE. Trans. Syst., Man Cyber., 23(3), pp. 665-685 (1993).
41. Jang, J.S.R. and Sun, C.T. Neuro-fuzzy modelling and control, Proc. IEEE, 83(3), pp. 378-406 (1995).
42. Jang, J.S.R., Sun, C.T. and Mizutani, E., Neuro-Fuzzy and Soft Computing, Prentice-Hall, Englewood Cliffs, NJ (1997).
43. Chang, F.J. and Chen, Y.C. Estuary water-stage forecasting by using radial basis function neural network, J. Hydrol., 270, pp. 158-166 (2003).