Liquefaction prediction using rough set theory

Document Type : Research Note

Authors

1 Department of Civil Engineering, University of Guilan, Rasht, P.O. Box 3756, I.R. Iran

2 Department of Civil Engineering, University of Guilan, Rasht, I.R. Iran

Abstract

Evaluation of liquefaction is one of the most important issues in geotechnical engineering. Liquefaction prediction depends on many factors and the relationship between these factors is non-linear and complex. Different methods have been proposed by different authors for liquefaction prediction. These methods are mostly based on statistical approaches and neural network.
In this paper a new approach based on Rough Set data mining procedure is presented for liquefaction prediction. The Rough set theory is a mathematical approach for analysis of imperfect knowledge or unclear description of objects. In this approach the decision rules are derived from conditional attributes in Rough Set analysis and the results are compared with actual field observations. The results of this study indicate that using this method can be helpful for liquefaction prediction and can reduce unnecessary costs in site investigation process.

Keywords

Main Subjects

References

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Scientia Iranica
Volume 26, Issue 2 - Serial Number 2
Transactions on Civil Engineering (A)
March and April 2019
Pages 779-788

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History

  • Receive Date: 07 January 2015
  • Revise Date: 15 July 2017
  • Accept Date: 16 October 2017

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