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http://dx.doi.org/10.7734/COSEIK.2019.32.2.93

A Propose on Seismic Performance Evaluation Model of Slope using Artificial Neural Network Technique  

Kwag, Shinyoung (Structural and Seismic Safety Research Team, Korea Atomic Energy Research Institute)
Hahm, Daegi (Structural and Seismic Safety Research Team, Korea Atomic Energy Research Institute)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.32, no.2, 2019 , pp. 93-101 More about this Journal
Abstract
The objective of this study is to develop a model which can predict the seismic performance of the slope relatively accurately and efficiently by using artificial neural network(ANN) technique. The quantification of such the seismic performance of the slope is not easy task due to the randomness and the uncertainty of the earthquake input and slope model. Under these circumstances, probabilistic seismic fragility analyses of slope have been carried out by several researchers, and a closed-form equation for slope seismic performance was proposed through a multiple linear regression analysis. However, a traditional statistical linear regression analysis has shown a limit that cannot accurately represent the nonlinearistic relationship between the slope of various conditions and seismic performance. In order to overcome these problems, in this study, we attempted to apply the ANN to generate prediction models of the seismic performance of the slope. The validity of the derived model was verified by comparing this with the conventional multi-linear and multi-nonlinear regression models. As a result, the models obtained through the ANN basically showed excellent performance in predicting the seismic performance of the slope, compared to the models obtained by the statistical regression analyses of the previous study.
Keywords
slope; seismic performance evaluation; probabilistic approach; artificial neural network;
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Times Cited By KSCI : 2  (Citation Analysis)
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