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《Chinese Journal of Rock Mechanics and Engineering》 2003-10
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Zhao Hongbo,Feng Xiating ( Key Laboratory of Rock and Soil Mechanics,Institute of Rock and Soil Mechanics, The Chinese Academy of Sciences, Wuhan 430071 China)  
An evolutionary support vector machine for displacement back analysis is proposed by combining the support vector machine and genetic algorithm. The learning and testing samples produced in orthogonal and equality experiment are used to train the support vector machine whose parameter is determined in global optimal by genetic algorithm. Thus,the support vector machine with optimal parameter is used to describe the relationship between the rock mechanics parameters and displacements. Then genetic algorithm is adopted again to search for the optimal rock mechanics parameters in their global ranges. As an example,a back analysis for elastic and elasto-plastic problem is introduced. The results are satisfactory.
【Fund】: 中国科学院知识创新重要项目(KJCX2-SW-L1-3);; 国家自然科学基金(50179034);; 国家重点基础研究发展规划(973)项目(2002CB412708)资助。
【CateGory Index】: TU452
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