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提出遗传双重互易法,利用遗传矩阵结构(Hierarchical Matrices,H-Matrices)加速双重互易边界元法(DRBEM)结构特征值问题分析过程并压缩数据存储.通过自适应交叉拟合算法对遗传矩阵中的相容子块使用低阶秩块拟合,减少参与矩阵运算数据规模,降低计算消耗的内存空间.针对规模和效率的不同计算环境要求提出两种求解优化策略,即完全遗传双重互易法(PHDM)和混合遗传双重互易法(MHDM),以求针对性提高数值计算效果.数值算例验证了所提方法的效率以及数据压缩效果.
Hierarchical Matrices (Hierarchy Matrices) are used to speed up the process of eigenvalue analysis of the double reciprocal boundary element method (DRBEM) and to compress the data storage.Analyzing the genetic matrices by adaptive cross-fitting algorithm , The lower-order rank block fitting is used to reduce the size of the data involved in the matrix operation and reduce the memory space for calculating the consumption.Secondly, two optimization strategies are proposed according to different computing environments such as scale and efficiency, that is, (PHDM) and Hybrid Hereditary Mutual Reciprocity (MHDM) in order to improve the efficiency of numerical calculation.The numerical example shows the efficiency of the proposed method and the effect of data compression.