Optimization of material parameter identification in biomechanics
作者： N. Harb , N. Labed , M. Domaszewski , F. Peyraut
DOI: 10.1007/S00158-013-0973-Y
关键词: Genetic algorithm 、 Parameter identification problem 、 Engineering 、 Genetics algorithms 、 Mathematical optimization 、 Meta-optimization 、 Algorithm 、 Estimation theory 、 Engineering design process 、 Identification (information)
摘要: The aim of this paper is to present an original and efficient approach for indentifying material parameter in biomechanics. A new method named GAO (Genetic algorithms & Analytical Optimization) addresses the identification problem that formulated as a non-linear least-squares problem. To evaluate technique, 7 parameters specific biomechanical law approached by multiple (genetic gradient-based methods). This comparative demonstrates rapidity efficiency estimation. It also explains behaviour genetic algorithms, their operators, advantages brings genetics leading successful identification.
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