Decision tree approach for soil liquefaction assessment.
In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view.
Department of Civil Engineering, The University of Akron, Akron, OH 44325, USA.
Amir H
AH
Gandomi
Department of Statistics, The University of Akron, Akron, OH 44325, USA.
Mark M
MM
Fridline
Department of Civil Engineering, The University of Akron, Akron, OH 44325, USA.
David A
DA
Roke
D003663:Decision Trees; D055866:Earthquakes; D008962:Models, Theoretical; D012987:Soil
D012987:Soil