Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data


Hanna A. M. , Ural D., Saygili G.

SOIL DYNAMICS AND EARTHQUAKE ENGINEERING, vol.27, no.6, pp.521-540, 2007 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 6
  • Publication Date: 2007
  • Doi Number: 10.1016/j.soildyn.2006.11.001
  • Title of Journal : SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
  • Page Numbers: pp.521-540

Abstract

Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. Derived from several field and laboratory tests, various simplified procedures such as stress-based, strain-based, Chinese criteria, etc. have been developed by utilizing case studies and undisturbed soil specimens. In order to address the collective knowledge built up in conventional liquefaction engineering, an alternative general regression neural network model is proposed in this paper.