z-logo
open-access-imgOpen Access
Simulating the Stress-Strain Relationship of Geomaterials by Support Vector Machine
Author(s) -
Zhao Hong,
Zenghui Huang,
Zhengsheng Zou
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/482672
Subject(s) - support vector machine , artificial neural network , nonlinear system , representation (politics) , constitutive equation , stress (linguistics) , stress–strain curve , computer science , artificial intelligence , engineering , structural engineering , finite element method , physics , linguistics , philosophy , quantum mechanics , politics , political science , law
Stress-strain relationship of geomaterials is important to numerical analysis in geotechnical engineering. It is difficult to be represented by conventional constitutive model accurately. Artificial neural network (ANN) has been proposed as a more effective approach to represent this complex and nonlinear relationship, but ANN itself still has some limitations that restrict the applicability of the method. In this paper, an alternative method, support vector machine (SVM), is proposed to simulate this type of complex constitutive relationship. The SVM model can overcome the limitations of ANN model while still processing the advantages over the traditional model. The application examples show that it is an effective and accurate modeling approach for stress-strain relationship representation for geomaterials

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom