Support vector regression based modeling of pier scour using field data

Engineering Applications of Artificial Intelligence

Volumn 24, Issue 5, 2011, Pages 911-916

  Pal, Mahesh ^a   Singh, N K ^b   Tiwari, N K ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^b BIT   (India)

Author keywords

Field scour data; Froehlich equation; HEC 18 equation; Neural network; Pier scour; Support vector machines

Indexed keywords

A-COEFFICIENT; BACK PROPAGATION NEURAL NETWORKS; DATA SETS; EMPIRICAL RELATIONS; FIELD DATA; FIELD SCOUR DATA; FROEHLICH EQUATION; GENERALIZED REGRESSION NEURAL NETWORKS; HEC-18 EQUATION; LOCAL SCOUR; MODELING APPROACH; PIER SCOUR; PIER WIDTH; POLYNOMIAL KERNELS; PREDICTIVE EQUATIONS; RADIAL BASIS; RADIAL BASIS FUNCTIONS; ROOT MEAN SQUARE ERRORS; SCOUR DEPTH; SUPPORT VECTOR REGRESSIONS;

ALGORITHMS; BACKPROPAGATION; BRIDGE PIERS; MEAN SQUARE ERROR; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; SCOUR; SENSITIVITY ANALYSIS; SUPPORT VECTOR MACHINES; VECTORS;

NEURAL NETWORKS;

EID: 79956110047     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2010.11.002     Document Type: Article

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