Predicting optimum parameters of a protective spur dike using soft computing methodologies - A comparative study

[1]  Dong-Sheng Jeng,et al.  Neural Network Modeling for Estimation of Scour Depth Around Bridge Piers , 2007 .

[2]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[3]  E. W. Lane Stable Channels in Erodible Materials , 1937 .

[4]  Shahaboddin Shamshirband,et al.  Adaptive neuro-fuzzy optimization of wind farm project net profit , 2014 .

[5]  Dong-Sheng Jeng,et al.  Predictions of bridge scour: Application of a feed-forward neural network with an adaptive activation function , 2013, Eng. Appl. Artif. Intell..

[6]  Shahaboddin Shamshirband,et al.  Adaptive neuro-fuzzy prediction of the optimum parameters of protective spur dike , 2014, Natural Hazards.

[7]  Masoud Ghodsian,et al.  Local Scour at Permeable Spur Dikes , 2008 .

[8]  Kourosh Behzadian,et al.  Protective spur dike for scour mitigation of existing spur dikes , 2011 .

[9]  K. Behzadian,et al.  Reduction of Local Scouring with Protective Spur Dike , 2008 .

[10]  M. A. Gill Erosion of Sand Beds around Spur Dikes , 1972 .

[11]  Mahmud Güngör,et al.  Generalized Regression Neural Networks and Feed Forward Neural Networks for prediction of scour depth around bridge piers , 2009, Adv. Eng. Softw..

[12]  David C. Froehlich Local Scour at Bridge Abutments , 1989 .

[13]  Shahaboddin Shamshirband,et al.  Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks , 2014, Eng. Appl. Artif. Intell..

[14]  Nabil A. Zaghloul,et al.  Local scour around spur-dikes , 1983 .

[15]  Chuntian Cheng,et al.  Using support vector machines for long-term discharge prediction , 2006 .

[16]  Alireza Keshavarzi,et al.  Prediction of scouring around an arch-shaped bed sill using Neuro-Fuzzy model , 2012, Appl. Soft Comput..

[17]  Andrew P. Bradley,et al.  Rule extraction from support vector machines: A review , 2010, Neurocomputing.

[18]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[19]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[20]  Mahesh Pal,et al.  Support vector regression based modeling of pier scour using field data , 2011, Eng. Appl. Artif. Intell..

[21]  Maziar Palhang,et al.  Generalization performance of support vector machines and neural networks in runoff modeling , 2009, Expert Syst. Appl..

[22]  S. M. Bateni,et al.  Neural network and neuro-fuzzy assessments for scour depth around bridge piers , 2007, Eng. Appl. Artif. Intell..

[23]  Hossein Basser,et al.  Local scour around complex pier groups and combined piles at semi-integral bridge , 2014 .

[24]  Abdollah Ardeshir,et al.  Verification of numerical study of scour around spur dikes using experimental data , 2014 .

[25]  Hao Zhang,et al.  Study on Flow and Bed Evolution in Channels with Spur Dykes , 2005 .

[26]  C. W. Chan,et al.  Modelling of river discharges and rainfall using radial basis function networks based on support vector regression , 2003, Int. J. Syst. Sci..

[27]  Stanley R. Davis,et al.  Evaluating scour at bridges. , 1995 .

[28]  J. C. Stevens,et al.  Discussion of Stable Channels in Erodible Materials by E. W. Lane , 1937 .

[29]  D. Husain,et al.  Local Scour at Bridge Abutments , 1998 .

[30]  R. Garde,et al.  Study of Scour Around Spur-Dikes , 1961 .

[31]  Shahaboddin Shamshirband,et al.  Support vector regression methodology for wind turbine reaction torque prediction with power-split hydrostatic continuous variable transmission , 2014 .

[32]  Shie-Yui Liong,et al.  FLOOD STAGE FORECASTING WITH SUPPORT VECTOR MACHINES 1 , 2002 .

[33]  Lawrence F. Pratt Flow Losses in the Lower Gila River , 1960 .

[34]  Mat Kiah M.L.,et al.  Wind turbine power coefficient estimation by soft computing methodologies: Comparative study , 2014 .

[35]  Hajime Nakagawa,et al.  Scour around Spur Dyke: Recent Advances and Future Researches , 2008 .

[36]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[37]  Mahesh Pal,et al.  Modelling pile capacity using Gaussian process regression , 2010 .

[38]  Shie-Yui Liong,et al.  Forecasting of hydrologic time series with ridge regression in feature space , 2007 .

[39]  Willi H. Hager,et al.  Spur Failure in River Engineering , 2008 .

[40]  Xiaowei Yang,et al.  The one-against-all partition based binary tree support vector machine algorithms for multi-class classification , 2013, Neurocomputing.

[41]  Shahaboddin Shamshirband,et al.  Adaptive neuro-fuzzy selection of the optimal parameters of protective spur dike , 2014, Natural Hazards.

[42]  Mushtaq Ahmad Experiments On Design And Behavior Of Spur Dikes , 1953 .

[43]  Ainuddin Wahid Abdul Wahab,et al.  Adaptive neuro-fuzzy maximal power extraction of wind turbine with continuously variable transmission , 2014 .

[44]  Mohammad Mohammadhassani,et al.  Application of ANFIS and LR in prediction of scour depth in bridges , 2014 .

[45]  Mahesh Pal,et al.  Application of support vector machines in scour prediction on grade-control structures , 2009, Eng. Appl. Artif. Intell..

[46]  Hua Li Countermeasures against scour at bridge abutments , 2005 .