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Predicting Bridge Pier Scour Depth With Svm

Authors: Arun Goel;

Predicting Bridge Pier Scour Depth With Svm

Abstract

{"references": ["G. W. Parker, L. Bratton, and, D. S. Armstrong, \"Stream stability and\nscour assessments at bridges in Massachusetts,\" U.S. Geological Survey\nOpen File Report No. 97-588 (CD-ROM), Massachusetts Highway Dept.\nBridge Section, Marlborough, Mass., Rep. .53, 1997.", "D. M. Sheppard, B. Melville, and H. Demir, \"Evaluation of existing\nequations for local scour at bridge piers.\" Journal of Hydraulic Engg.,\n2014,140(01), pp 14-23.", "T. L. Lee, D.S. Jeng and J.H. Hong, \"Neural network modeling for scour\ndepth around bridge piers,\" Journal of Hydrodynamics, Vol. 19(3), pp.\n378-386, 2007.", "Lu Deng and C.S. Cai, \"Bridge scour; prediction, modelling, monitoring,\nand countermeasures-review,\" Journal of Practice periodical structural\ndesign and construction, ASCE, Vol. 15(2), pp. 125-134, 2010.", "R. E. Ettema, B.W. Melville and B. Barkdoll, \"Closure. A scale effect in\npier-scour experiments,\" Journal of Hydraulic Engineering, ASCE, Vol.\n125(8), pp.895-896, 1999.", "E. M. Laursen and A. Toch, \"Scour around bridge piers and abutments,\"\nIowa Highway Research Board, Vol. 4, pp. 60, 1956.", "H. W. Shen (1971). Scour near piers. In: River Mechanics, II, Chap. 23,\nFt. Collins, Colo.", "Breusers, H. N. C., Nicollet, G., and Shen, H. W. \"Local scour around\ncylindrical piers.\" Journal of Hydraulcs Research, 15 (3), 211-252,\n1977.", "Hancu, S. Sur le calcul des affouillements locaux dams la zone des piles\ndes ponts. Proc., 14th IAHR Congress, Paris, France, 3,. 299-313,1971.\n[10] U.S. DOT. \"Evaluating scour at bridges\". Hydraul. Eng. Circular No.18,\nFHWA-IP-90- 017, Fed. Hwy. Admin., U.S. Dept. of Transp., McLean,\nVa.1993. [11] M. Pal, N. K.Singh, and N. K. Tiwari, \"Support vector regression based\nmodeling of pier scour using field data\", Journal of Engineer\nApplications of Artificial Intelligence, 24(5), 911-916, 2011.\n[12] J. Hong, M. Goyal, Y. Chiew, and L. Chua, \"Predicting time-dependent\npier scour depth with support vector regression\", Journal of Hydrology,\n468-469, 241-248, 2012.\n[13] Mahesh Pal, N.K. Singh and N.K. Tiwari, \"Pier scour modelling using\nrandom forest regression\". ISH Journal of Hydraulic Engineering,\nVolume 19, Issue 2, pages 69-75, 2013.\n[14] M. Pal, N. K. Singh, and N. K. Tiwari, \"Kernel methods for pier scour\nmodeling using field data \" Journal of Hydroinformatics, Vol. 16, No. 4,\npp 784\u2013796,2014.\n[15] I. Kim, M. Fard, and A. Chattopadhyay, \"Investigation of a Bridge Pier\nScour Prediction Model for Safe Design and Inspection\". Journal of\nBridge Engg, 10.1061/(ASCE)BE.1943-5592.0000677,04014088.just\nreleased,2014.\n[16] Min-Yuan Cheng and Minh-Tu Cao, \"Hybrid intelligent inference model\nfor enhancing prediction accuracy of scour depth around bridge piers\".\nJournal of Structure and Infrastructure Engineering: Maintenance,\nManagement, Life-Cycle Design and Performance.\nttp://dx.doi.org/10.1080/15732479.2014.939089,2014.\n[17] Vapnik, V. N., The Nature of Statistical Learning Theory. New York:\nSpringer-Verlag 1995.\n[18] Vapnik, V. N. Statistical Learning Theory. New York: John Wiley and\nSons, 1998.\n[19] Smola, A. J. Regression estimation with support vector learning\nmachines. Master's Thesis, Technische Universit\u00e4t M\u00fcnchen, Germany,\n1996.\n[20] Cortes, C., and Vapnik, V. N. Support Vector Networks, Machine\nLearning. 20, pp 273-297, 1995.\n[21] Leunberger, D,. Linear and Nonlinear Programming. Addison-Wesley,\n1984.\n[22] U. C. Kothyari, R. J. Garde and K. G. Range Raju, \"Temporal variation\nof scour around circular bridge piers,\" J. Hydr. Eng., Vol. 118(8), pp.\n1091-1106, 1992.\n[23] D-S Jeng,S. M. Bateni, E. Lockett,\" Neural network assessment for\nscour depth around bridge piers\", Research Report No R855,\nDepartment of Civil Engineering, Sydney, AUSTRALIA, November,\n2005.,http://www.civil.usyd.edu.au/.\n[24] Weka software version 3.4.13 http://www.cs.waikato.ac.nz/~ml/weka/."]}

Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly & Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly & Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicate the improvement in the performance of SVM (Poly & Rbf) in comparison to dimensional form of scour.

Keywords

SVM (Poly & Rbf kernels)., pier scour, SVM (Poly & Rbf kernels)., Modeling, regression, prediction

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