期刊
APPLIED MATHEMATICAL MODELLING
卷 33, 期 10, 页码 3997-4012出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2009.01.011
关键词
Back analysis; Geomechanical parameters identification; Support vector machine; Particle swarm optimization
资金
- University (NCET)
- Doctoral Fund of Henan Polytechnic University [648197]
Back analysis is commonly used in identifying geomechanical parameters based on the monitored displacements. Conventional back analysis method is not capable of recognizing non-linear relationship involving displacements and mechanical parameters effectively. The new intelligent displacement back analysis method proposed in this paper is the combination of support vector machine, particle swarm optimization, and numerical analysis techniques. The non-linear relationship is efficiently represented by support vector machine. Numerical analysis is used to create training and testing samples for recognition of SVMs. Then, a global optimum search on the obtained SVMs by particle swarm optimization can lead to the geomechanical parameters identification effectively. (C) 2009 Elsevier Inc. All rights reserved.
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