Location

Arlington, Virginia

Session Start Date

8-11-2008

Session End Date

8-16-2008

Abstract

The surface of the earth is very rarely flat and so there are slopes nearly everywhere. The loads on slope are due to the self-weight of the soil and to external loads, which may come from foundation at the top and seismic loads. Geotechnical engineers have to pay particular attention to geology, ground water and shear strength of soils in assessing slop stability. Neural networks are very sophisticated modeling techniques, capable of modeling extremely complex functions. In particular, neural networks are non-linear. With respect to the above advantages, in this paper, artificial neural networks are developed to predict slope stability in a specified location. Then the results are compared with older analysis methods to check the ANN model’s validity.

Department(s)

Civil, Architectural and Environmental Engineering

Appears In

International Conference on Case Histories in Geotechnical Engineering

Meeting Name

Sixth Conference

Publisher

Missouri University of Science and Technology

Publication Date

8-11-2008

Document Version

Final Version

Rights

© 2008 Missouri University of Science and Technology, All rights reserved.

Document Type

Article - Conference proceedings

File Type

text

Language

English

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Prediction of Slope Stability Using Artificial Neural Network (Case Study: Noabad, Mazandaran, Iran)

Arlington, Virginia

The surface of the earth is very rarely flat and so there are slopes nearly everywhere. The loads on slope are due to the self-weight of the soil and to external loads, which may come from foundation at the top and seismic loads. Geotechnical engineers have to pay particular attention to geology, ground water and shear strength of soils in assessing slop stability. Neural networks are very sophisticated modeling techniques, capable of modeling extremely complex functions. In particular, neural networks are non-linear. With respect to the above advantages, in this paper, artificial neural networks are developed to predict slope stability in a specified location. Then the results are compared with older analysis methods to check the ANN model’s validity.