Estimation of liquefaction-induced horizontal displacements using artificial neural networks

M. Chiru-Danzer, C. H. Juang, R. A. Christopher, J. Suber

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

In the present study, artificial neural network (ANN) models based on field performance data are developed for predicting liquefaction-induced horizontal displacements. A database consisting of 443 measurements of horizontal displacements forms the basis for ANN modeling and analysis. The ANN model resulted in predictive capabilities that surpass those of published methods. A sensitivity analysis of the ANN model is conducted to evaluate the effect of each individual input variable on the calculated horizontal displacement. The newly developed ANN model is compared with and shown to be more accurate than other existing methods in predicting liquefaction-induced horizontal displacements.

Original languageEnglish
Pages (from-to)200-207
Number of pages8
JournalCanadian Geotechnical Journal
Volume38
Issue number1
DOIs
StatePublished - 2001

Keywords

  • Artificial neural networks
  • Lateral spreading
  • Liquefaction

Fingerprint

Dive into the research topics of 'Estimation of liquefaction-induced horizontal displacements using artificial neural networks'. Together they form a unique fingerprint.

Cite this