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Ground Movements Prediction in Shield-Driven Tunnels using Gene Expression Programming

Author(s):


Medium: journal article
Language(s): en 
Published in: The Open Construction and Building Technology Journal, , n. 1, v. 14
Page(s): 286-297
DOI: 10.2174/1874836802014010286
Abstract:

Introduction:

The increase in population and traffic in metropolitan areas has led to the development of underground transportation spaces. Therefore, the estimation of the surface settlement caused by the construction of underground structures should be accurately considered. Several methods have been developed to predict tunneling-induced surface settlement. Among these methods, artificial intelligence-based methods have received much attention in recent years. This paper is aimed to develop a model based on Gene Expression Programming (GEP) algorithm to predict surface settlement induced by mechanized tunneling.

Methods:

For this purpose, Tehran Metro Line 6 was simulated numerically to investigate the effects of different parameters on the surface settlement, and 85 datasets were prepared from numerical simulations. Subsequently, several GEP models were implemented using the obtained datasets from numerical simulations and finally, a model with 30 chromosomes and 3 genes was selected as the optimum model.

Results:

A comparison was made between obtained maximum surface settlements by the proposed GEP model and numerical simulation. The results demonstrated that the proposed model could predict surface settlement induced by mechanized tunneling with a high degree of accuracy.

Conclusion:

Finally, a mathematical equation was derived from the proposed GEP model, which can be easily used for surface settlement prediction.

Copyright: © 2020 A. Ramesh, M. Hajihassani, A. Rashiddel
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10443630
  • Published on:
    05/10/2020
  • Last updated on:
    02/06/2021