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Mathematical Problems in Engineering
Volume 2013, Article ID 980154, 11 pages
http://dx.doi.org/10.1155/2013/980154
Research Article

A Nonlinear Optimization Technique of Tunnel Construction Based on DE and LSSVM

1School of Resources & Civil Engineering, Northeastern University, Shenyang 110004, China
2Highway and Bridge Engineering Institute, Dalian Maritime University, Dalian 116026, China

Received 22 November 2012; Revised 10 February 2013; Accepted 23 February 2013

Academic Editor: Shengyong Chen

Copyright © 2013 Xing Jun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Tunnel construction is a dynamic controlling system with observability and controllability; the feedback analysis requires identifying geophysics parameters and adjusting supporting parameters, and both of them are optimisation problems. The paper proposed a nonlinear optimization technique based on difference evolution arithmetic (DEA), least square support vector machine (LSSVM), and three dimensional numerical simulation. This method employs support vector machine with optimal architecture trained by the difference evolution arithmetic, instead of the time-consuming finite element analysis. Firstly, the three dimensional numerical simulation is used to create training and testing samples for LSSVM model construction. Then the nonlinear relationship between rock or anchoring parameters and displacement is constructed by support vector machine. Finally, the geophysics and supporting parameters are obtained by DE optimization arithmetic. The technique overcomes the conventional optimization method shortages of expending too much computing time and easily being limited in local optimal solution. This technique was verified by applying it to the feedback analysis of Dalian Metro in China, and the influence of the parameters of LSSVM and DE on the simulation ability of the algorithm was investigated.