Neuro-fuzzy GMDH systems based evolutionary algorithms to predict scour pile groups in clear water conditions

Ocean Engineering

Volumn 99, Issue , 2015, Pages 85-94

  Najafzadeh, Mohammad ^a  

^a GRADUATE UNIVERSITY OF ADVANCED TECHNOLOGY   (Iran)

Author keywords

Clear water; Evolutionary algorithms; Neuro fuzzy group method of data handling; Pile groups; Scour depth

Indexed keywords

ALGORITHMS; BRIDGE PIERS; DATA HANDLING; EVOLUTIONARY ALGORITHMS; EXPERIMENTAL REACTORS; FORECASTING; FUZZY INFERENCE; FUZZY SETS; PARTICLE SWARM OPTIMIZATION (PSO); SCOUR; SENSITIVITY ANALYSIS;

CRITICAL FLOW CONDITIONS; DIMENSIONAL PARAMETERS; FUNCTIONAL RELATIONSHIP; GRAVITATIONAL SEARCH ALGORITHM (GSA); GROUP METHOD OF DATA HANDLING; NEURO-FUZZY; PILE GROUPS; SCOUR DEPTH;

PILES;

ALGORITHM; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; FUZZY MATHEMATICS; OPTIMIZATION; PILE GROUP; SCOUR; SENSITIVITY ANALYSIS;

EID: 84926039215     PISSN: 00298018     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.oceaneng.2015.01.014     Document Type: Article

References (58)

1. A. Amini, B.W. Mellvile, T.M. Ali, and A.H. Ghazali Clear-water local scour around pile groups in shallow-water flow J. Hydraul. Eng. 138 2 2012 177 185
2. B. Ataie-Ashtiani, Z. Baratian-Ghoroghi, and A.A. Beheshti Experimental investigation of clear-water local scour of compound piers J. Hydraul. Eng. 136 6 2010 343 351
3. R.E. Abdel-Aal, and E.-S.M. El-alfy Constructing optimal educational tests using GMDH-based item ranking and selection Neurocomputing 72 2009 1184 1197
4. N. Amanifard, N. Nariman-Zadeh, M.H. Farahani, and A. Khalkhali Modeling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks J. Energy Convers. Manag. 49 10 2008 2588 2594
5. V.P. Astakhov, and V.V. Glitsky Tool life testing in gundrilling: an application of the group method of data handling (GMDH) Int. J. Mach. Tools Manuf. 45 2005 509 517
6. B. Ataie-Ashtiani, and A.A. Beheshti Experimental investigation of clear-water local scour at pile groups J. Hydraul. Eng. 132 10 2006 1100 1104
7. A.A. Beheshti, and B. Ataie-Ashtiani Experimental study of three-dimensional flow field around a complex bridge pier J. Hydraul. Eng. 136 2 2010 143 154
8. N.H.C. Breusers, and A.J. Raudkivi IAHR, Hydraulic Structure Design Manual: Scouring vol. 2 1991 Balkema Rotterdam, Netherlands
9. S.M. Bateni, and D.S. Jeng Estimation of pile group using adaptive neuro-fuzzy approach Ocean Eng. 34 2007 1344 1354
10. S.E. Coleman Clear-water local scour at complex piers J. Hydraul. Eng., ASCE 131 4 2005 330 334
11. S. Dey, S.K. Bose, and G.L.N. Sastry Clear-water scour at circular piers: a model J. Hydraul. Eng. 121 12 1995 869 876
12. S. Dey, R.V. Raikar, and A. Roy Scour at submerged cylindrical obstacles under steady flow J. Hydraul. Eng. 134 1 2008 105 109
13. Donguang, G., Lillian, G.P., Carl, F.N. Pier Scour Equations Used in the Peoples Republic of China. Unpublished paper submitted to FHWA, April 1994.
14. A. Etemad-Shahidi, and N. Ghaemi Model tree approach for prediction of pile groups scour due to waves Ocean. Eng. 38 2011 1522 1527
15. D. Ferraro, A. Tafarojnoruz, R. Gaudio, and A.H. Cardoso Effects of pile cap thickness on the maximum scour depth at a complex pier J. Hydraul. Eng. - ASCE 139 5 2013 482 491
16. N. Ghaemi, A. Etemad-Shahidi, and B. Ataie-Ashtiani Estimation of current-induced pile groups scour using a rule based method J. Hydroinform. 15 2013 516 528
17. S. Ghazanfari-Hashemi, A. Etemad-Shahidi, M.H. Kazeminezhad, and A.R. Mansoori Prediction of pile groups scour in waves using support vector machines and ANN J. Hydroinform. 13 2011 609 620
18. R. Gaudio, A. Tafarojnoruz, and S. De Bartolo Sensitivity analysis of bridge pier scour depth predictive formulae J. Hydroinform. 15 3 2013 939 951
19. C.R. Hannah Scour at Pile Groups. Research Report no.28-3 1978 Civil Engineering Department, University of Canterbury Christchurch, New Zealand
20. H.-S. Hwang Fuzzy GMDH-type neural network model and its application to forecasting of mobile communication Comput. Ind. Eng. 50 2006 450 457
21. A. Jamali, N. Nariman-Zadeh, A. Darvizeh, A. Masoumi, and S. Hamrang Multi-objective evolutionary optimization of polynomial neural networks for modelling and prediction of explosive cutting process Eng. Appl. Artif. Intell. 22 2009 676 687
22. Kennedy, J., Eberhart, R.C., 1995. Particle swarm optimization. In: Proceedings of the fourth IEEE International Conference on Neural Networks, pp. 1942-1948.
23. A.R. Kambekar, and M.C. Deo Estimation of pile group using neural networks Appl. Ocean Res. 25 4 2003 225 234
24. F. Kalantary, H. Ardalan, and N. Nariman-Zadeh An investigation on the Su-NSPT correlation using GMDH type neural networks and genetic algorithms Eng. Geol. 104 1-2 2009 144 155
25. C. Li, and J. Zhou Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm Energy Convers. Manag. 52 2011 374 381
26. H.R. Madala, and A.G. Ivakhnenko Inductive Learning Algorithms for Complex Systems Modeling 1994 CRC Press Boca Raton, FL
27. M. Mehrara, A. Moeini, M. Ahrari, and A. Erfanifard Investigating the efficiency in oil futures market based on GMDH approach Expert Syst. Appl. 36 4 2009 7479 7483
28. B.W. Melville, and A.J. Sutherland Design method for local scour at bridge piers J. Hydraul. Eng. 114 10 1988 1210 1226
29. B.W. Melville, and S.E. Coleman Bridge Scour 2000 Water Resources Publications Highlands Ranch, CO
30. N.E. Mitrakis, J.B. Theocharis, and V. Petridis A multilayered neuro-fuzzy classifier with self-organizing properties Fuzzy Sets Syst. 159 23 2008 3132 3159
31. N.E. Mitrakis, and J.B. Theocharis A diversity-driven structure learning algorithm for building hierarchical neuro-fuzzy classifiers Information Sci. 186 1 2012 40 58
32. A. Mozaffari, A. Fathi, and S. Behzadipour An evolvable self-organizing neuro-fuzzy multilayered classifier with group method data handling and grammar-based bio-inspired supervisors for fault diagnosis of hydraulic systems Int. J. Intell. Comput. Cybern. 7 2014 38 78
33. K. Nagasaka, H. Ichihashi, and R. Leonard Neuro-fuzzy GMDH and its application to modeling grinding characteristics Int. J. Prod. Res. 33 5 1995 1229 1240
34. M. Najafzadeh, and G.A. Barani Comparison of group method of data handling based genetic programming and back propagation systems to predict scour depth around bridge piers Sci. Iran. Trans. (A) 18 6 2011 1207 1213
35. M. Najafzadeh, and H.Md. Azamathulla Group method of data handling to predict scour depth around bridge piers Neural Comput. Appl. 23 7-8 2013 2107 2112
36. M. Najafzadeh, and H.Md. Azamathulla Neuro-fuzzy GMDH systems to predict the scour pile groups due to waves J. Comput. Civ. Eng. ASCE 2013 10.1061/(ASCE)CP.1943-5487.0000376
37. M. Najafzadeh, Gh-A. Barani, and H. Md. Azamathulla Prediction of Pipeline Scour Depth in Clear-Water and Live-Bed Conditions using GMDH Neural Computing, Springer, 24 3-4 2014 629 635
38. M. Najafzadeh, G.A. Barani, and M.R. Hessami Kermani Aboutment scour in live-bed and clear-water using GMDH network Water Sci. Technol. 67 5 2013 1121 1128
39. M. Najafzadeh, G.A. Barani, and H.M.d. Azamathulla. GMDH to prediction of scour depth around vertical piers in cohesive soils Appl. Ocean. Res. 40 2013 35 41
40. M. Najafzadeh, G.A. Barani, and M.R. Hessami Kermani GMDH network based back propagation algorithm to predict abutment scour in cohesive soils Ocean Eng. 59 2013 100 106
41. M. Najafzadeh, G.A. Barani, and M.R. Hessami-Kermani Group method of data handling to predict scour depth around vertical piles under regular waves Sci. Iran. 20 3 2013 406 413
42. M. Najafzadeh, and S.Y. Lim Application of improved neuro-fuzzy GMDH to predict scour depth at sluice gates Earth Sci. Informatics. 18 1 2015 187 196
43. G.C. Onwubolu Design of hybrid differential evolution and group method in data handling networks for modeling and prediction Inf. Sci. 178 2008 3618 3634
44. E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi Filter modeling using gravitational search algorithm Eng. Appl. Artif. Intell. 24 1 2011 117 122
45. E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi GSA: a gravitational search algorithm Inf. Sci. 179 2009 2232 2248
46. Richardson, E.V., Harrison, L.J., Richardson, J.R. Davis, S.R., 2003. Evaluating Scour at Bridges. Federal Highway Administration Hydraulic Engineering Circular No. 18 (HEC-18), second edition. Publication FHWA-IP-90-017 (revised April 1993).
47. A.M. Sattar Gene expression models for the prediction of longitudinal dispersion coefficients in transitional and turbulent pipe flow J. Pipeline Syst. Eng. Pract. ASCE 5 1 2014 04013011
48. A.M. Sattar Gene expression models for prediction of dam breach parameters J. Hydroinform. 16 3 2014 550 571
49. M. Salim, and J.S. Jones Scour Around Exposed Pile Foundations. Compilation of Conference Scour Papers (1991-1998) 1996 ASCE Reston, VA
50. D.M. Sheppard, M. Odeh, and T. Glasser Large scale clear-water local pier scour experiments J. Hydraul. Eng., ASCE, 114 10 2004 1210 1226
51. D. Srinivasan Energy demand prediction using GMDH networks Neurocomputing 72 2008 625 629
52. Shi, Y., Eberhart, R.C., 1998. A modified swarm optimizer. In: Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, pp. 69-73.
53. E. Salajegheh, S. Gholizadeh, and M. Khatibinia Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method Earthq. Eng. Eng. Vib. 7 1 2008 14 24
54. E. Salajegheh, J. Salajegheh, S.M. Seyedpoor, and M. Khatibinia Optimal design of geometrically nonlinear space trusses using adaptive neuro-fuzzy inference system Sci. Iran. 16 5 2009 403 414
55. O. Takashi, I. Hidetomo, M. Tetsuya, and N. Kazunori Orthogonal and successive projection methods for the learning of neurofuzzy GMDH Inf. Sci. 110 1998 5 24
56. N. Vittal, U.C. Kothyari, and M. Haghighat Clear-water scour around bridge pier group J. Hydraul. Eng. 120 11 1994 1309 1318
57. M. Witczak, J. Korbicz, M. Mrugalski, and R. Patton A GMDH neural network-based approach to robust fault diagnosis: application to the DAMADICS benchmark problem Control Eng. Pract. 14 6 2006 671 683
58. M. Zounemat-Kermani, A.A. Beheshti, B. Ataie-Ashtiani, and S.R. Sabbagh-Yazdia Estimation of current-induced scour depth around pile groups using neural network and adaptive neuro-fuzzy inference system Appl. Soft Comput. 9 2 2009 746 755