摘要
介绍了一种新颖的群集智能优化算法—人工蜂群算法(ABCA),同时为提高算法的搜索效率,引入Nelder-Mead单纯形算法,提出了一种用于材料参数反演分析的混合单纯形人工蜂群算法。将所提出的算法用于混凝土重力坝动力材料参数识别,建立了基于不完全模态测试数据动力材料参数识别的优化反演模型。算例分析表明,混合算法融合了两种算法的优点,具有收敛速度快、识别精度高等特点,是一种高效的系统优化和参数识别方法。
The hybrid simplex artificial bee colony algorithm which combines artificial bee colony algorithm with the Nelder-Mead simplex search method for improving the search efficiency in computation is proposed. The algorithm is applied to identify the material dynamic parameters of concrete dams by establishing an optimization inverse calculation model based on incomplete modal test data. Application example shows that the proposed algorithm possesses the advantages of both artificial bee colony algorithm and Nelder-Mead simplex search method, which have the features of quick convergence and high accuracy of identification.
出处
《水利学报》
EI
CSCD
北大核心
2009年第6期736-742,共7页
Journal of Hydraulic Engineering
基金
教育部创新团队资助项目(IRT0518)
关键词
混凝土坝
动力材料参数
反演分析
人工蜂群算法
Nelder-Mead单纯形算法
模态参数
concrete dam
material dynamic parameter
optimization reverse calculation model
artificial bee colony algorithm
Nelder-Mead simplex search method
modal test
