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Paper Information

Journal:   MODARES TECHNICAL AND ENGINEERING   Winter 2004 , Volume - , Number 14; Page(s) 1 To 14.
 
Paper: 

THE APPLICATION OF NEURAL NETWORKS IN GEOTECHNICAL ENGINEERING: MODELING, ANALYSIS, AND DESIGN

 
 
Author(s):  BANIMAHD M., YASROBI S.S.*
 
* Civil Engineering Dept., Faculty of Engineering, T.M.U, Tehran, Iran
 
Abstract: 

Prediction of soil engineering behavior, based on previous experiments and observations, plays an important role in geotechnical engineering. So, to cover the subject, many researchers have focused on the mathematical and statistical models during the last decades. In this paper, multi-layer perceptron (MLP), a well-known method in Artificial Neural Networks, is used for modeling stress- strain behavior of silty sands, slop stability analysis of river bank and design of concrete liner of water tunnels. In addition, MLP design and factor affecting its performance have been discussed briefly. Since all different kinds of problems have been covered (Modeling, Analysis and Design), authors see immense potential for the application of well-trained neural networks in geotechnical engineering.

 
Keyword(s): NEURAL NETWORKS, GEOTECHNICAL ENGINEERING, STRESS-STRAIN, SLOP STABILITY, CONCRETE LINER
 
References: 
  • ندارد
 
  Persian Abstract Yearly Visit 84
 
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