Prediction of equilibrium scour depth in uniform non-cohesive sediments downstream of an apron using computational intelligence

References

• Azamathulla, H. M. D., Deo, M. C., & Deolalikar, P. B. (2008). Alternative neural networks to estimate the scour below spillways. Advances in Engineering Software, 39, 689–698.10.1016/j.advengsoft.2007.07.004
   Web of Science ®Google Scholar
• Azamathulla, H. M. D., & Ghani, A. A. (2011). ANFIS-based approach for predicting the scour depth at culvert outlets. Journal of Pipeline Systems Engineering and Practice, 2, 35–40.10.1061/(ASCE)PS.1949-1204.0000066
   Web of Science ®Google Scholar
• Azmathullah, H. M. D., Deo, M. C., & Deolalikar, P. B. (2005). Neural networks for estimation of scour downstream of a ski-jump bucket. Journal of Hydraulic Engineering, 131, 898–908.10.1061/(ASCE)0733-9429(2005)131:10(898)
   Web of Science ®Google Scholar
• Azmathullah, H. M. D., Deo, M. C., & Deolalikar, P. B. (2006). Estimation of scour below spillways using neural networks. Journal of Hydraulic Research, 44, 61–69.10.1080/00221686.2006.9521661
   Web of Science ®Google Scholar
• Balachandar, R., & Kells, J. A. (1997). Local channel in scour in uniformly graded sediments: The time-scale problem. Canadian Journal of Civil Engineering, 24, 799–807.10.1139/l97-034
   Web of Science ®Google Scholar
• Balachandar, R., & Kells, J. A. (1998). Instantaneous water surface and bed scour profiles using video image analysis. Canadian Journal of Civil Engineering, 25, 662–667.10.1139/l98-003
   Web of Science ®Google Scholar
• Balachandar, R., Kells, J. A., & Thiessen, R. J. (2000). The effect of tailwater depth on the dynamics of local scour. Canadian Journal of Civil Engineering, 27, 138–150.10.1139/l99-061
   Web of Science ®Google Scholar
• Bateni, S. M., Borghei, S. M., & Jeng, D. S. (2007). Neural network and neuro-fuzzy assessments for scour depth around bridge piers. Engineering Applications of Artificial Intelligence, 20, 401–414.10.1016/j.engappai.2006.06.012
   Web of Science ®Google Scholar
• Bateni, S. M., Jeng, D. S., & Melville, B. W. (2007). Bayesian neural networks for prediction of equilibrium and time-dependent scour depth around bridge piers. Advances in Engineering Software, 38, 102–111.10.1016/j.advengsoft.2006.08.004
   Web of Science ®Google Scholar
• Bunke, H., & Kandel, A. (2000). Neruro-fuzzy pattern recognition. Singapore: World Scientific.
   Google Scholar
• Chatterjee, S. S., & Ghosh, S. N. (1994). Local scour due to submerged horizontal jet. Journal of Hydraulic Engineering, 120, 973–992.10.1061/(ASCE)0733-9429(1994)120:8(973)
   Web of Science ®Google Scholar
• Chatterjee, S. S., Ghosh, S. N., & Chatterjee, M. (1980). Local scour due to submerged horizontal jet. Journal of the Hydraulics Division, 106, 1765–1782.
   Web of Science ®Google Scholar
• Choi, S. U., & Cheong, S. (2006). Prediction of local scour around bridge piers using artificial neural networks. Journal of the American Water Resources Association, 42, 487–494.10.1111/jawr.2006.42.issue-2
   Web of Science ®Google Scholar
• Dey, S., & Sarkar, A. (2006). Scour downstream of an apron due to submerged horizontal jets. Journal of Hydraulic Engineering, 132, 246–257.10.1061/(ASCE)0733-9429(2006)132:3(246)
   Web of Science ®Google Scholar
• Firat, M., & Gungor, M. (2009). Generalized regression neural networks and feed forward neural networks for prediction of scour depth around bridge piers. Advances in Engineering Software, 40, 731–737.10.1016/j.advengsoft.2008.12.001
   Web of Science ®Google Scholar
• Gallant, A. R., & White, H. (1992). On learning the derivatives of an unknown mapping with multilayer feedforward networks. Neural Networks, 5, 129–138.10.1016/S0893-6080(05)80011-5
   Web of Science ®Google Scholar
• Guven, A., & Gunal, M. (2008). Prediction of scour downstream of grade-control structures using neural networks. Journal of Hydraulic Engineering, 134, 1656–1660.10.1061/(ASCE)0733-9429(2008)134:11(1656)
   Web of Science ®Google Scholar
• Jang, J. S. R., & Sun, C. T. (1995). Neuro-fuzzy modeling and control. IEEE, Special Issue on Fuzzy Logic in Engineering Applications, 83, 378–406.
   Web of Science ®Google Scholar
• Jang, J. S. R., Sun, C. T., & Mizutani, E. (1997). Neuro-fuzzy and soft computing (pp. 510–514). Upper Sadd le River, NJ: Prentice Hall.
   Google Scholar
• Kambekar, A. R., & Deo, M. C. (2003). Estimation of pile group scour using neural networks. Applied Ocean Research, 25, 225–234.10.1016/j.apor.2003.06.001
   Web of Science ®Google Scholar
• Karami, H., Ardeshir, A., Saneie, M., & Salamatian, S. A. (2012). Prediction of time variation of scour depth around spur dikes using neural networks. Journal of Hydroinformatics, 14, 180–191.10.2166/hydro.2011.106
   Web of Science ®Google Scholar
• Kaya, A. (2010). Artificial neural network study of observed pattern of scour depth around bridge piers. Computers and Geotechnics, 37, 413–418.10.1016/j.compgeo.2009.10.003
   Web of Science ®Google Scholar
• Keshavarzi, A., Gazni, R., & Homayoon, S. R. (2012). Prediction of scouring around an arch-shaped bed sill using neuro-fuzzy model. Applied Soft Computing, 12, 486–493.10.1016/j.asoc.2011.08.019
   Web of Science ®Google Scholar
• Lee, T. L., Jeng, D. S., Zhang, G. H., & Hong, J. H. (2007). Neural network modeling for estimation of scour depth around bridge piers. Journal of Hydrodynamics, Series B, 19, 378–386.10.1016/S1001-6058(07)60073-0
   Web of Science ®Google Scholar
• Liriano, S. L., & Day, R. A. (2001). Prediction of scour depth at culvert outlets using neural networks. Journal of Hydroinformatics, 3, 231–238.
   Google Scholar
• Nik Hassan, N., & Narayanan, R. (1985). Local scour downstream of an apron. Journal of Hydraulic Engineering, 111, 1371–1384.10.1061/(ASCE)0733-9429(1985)111:11(1371)
   Web of Science ®Google Scholar
• Rahman, H. S., Alireza, K., & Reza, G. (2010). Application of artificial neural network, kriging, and inverse distance weighting models for estimation of scour depth around bridge pier with bed sill. Journal of Software Engineering and Applications, 3, 944–964.10.4236/jsea.2010.310112
   Google Scholar
• Şarlak, N., & Tiğrek, Ş. (2011). Analysis of experimental data sets for local scour depth around bridge abutments using artificial neural networks. Water SA, 37, 595–602.
   Web of Science ®Google Scholar
• Taylor, J. G. (1996). Neural networks and their applications. West Sussex: Wiley.
   Google Scholar
• Zounemat-Kermani, M., Beheshti, A. A., Ataie-Ashtiani, B., & Sabbagh-Yazdi, S. R. (2009). Estimation of current-induced scour depth around pile groups using neural network and adaptive neuro-fuzzy inference system. Applied Soft Computing, 9, 746–755.10.1016/j.asoc.2008.09.006
   Web of Science ®Google Scholar