Uplift capacity of suction caisson in clay using multivariate adaptive regression spline

Ocean Engineering

Volumn 38, Issue 17-18, 2011, Pages 2123-2127

  Samui, Pijush ^a   Das, Sarat ^b   Kim, Dookie ^c  

^a VIT UNIVERSITY   (India)

^b NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^c Kunsan National University   (South Korea)

Author keywords

Artificial neural network; Caisson; Multivariate adaptive regression spline; Uplift capacity

Indexed keywords

ARTIFICIAL NEURAL NETWORK; INCLINED ANGLE; LOAD APPLICATION; LOAD RATE; MODEL INPUTS; MULTIVARIATE ADAPTIVE REGRESSION SPLINE; MULTIVARIATE ADAPTIVE REGRESSION SPLINES; NON-PARAMETRIC; SOIL SURFACES; SUCTION CAISSON; UNDRAINED SHEAR STRENGTH; UPLIFT CAPACITY;

CAISSONS; FINITE ELEMENT METHOD; GEOLOGIC MODELS; HYDRAULIC STRUCTURES; NEURAL NETWORKS; PRESSURE VESSELS; REGRESSION ANALYSIS; SOIL MECHANICS;

FOUNDATIONS;

ARTIFICIAL NEURAL NETWORK; CAISSON; CLAY SOIL; FINITE ELEMENT METHOD; MULTIVARIATE ANALYSIS; REGRESSION ANALYSIS; SHEAR STRENGTH; SOIL STRENGTH; SOIL SURFACE; SOIL-STRUCTURE INTERACTION;

EID: 82555165786     PISSN: 00298018     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.oceaneng.2011.09.036     Document Type: Article

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