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Hybrid artificial fish school algorithm for solving ill-conditioned linear systems of equations

机译:求解等式不良线性系统的混合人工鱼学算法

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Based on particle swarm optimization (PSO) and artificial fish swarm algorithm (AFSA), a hybrid artificial fish swarm optimization algorithm is proposed. The novel method makes full use of the quickly local convergent performance of PSO and the global convergent performance of AFSA, and then is used for solving ill-conditioned linear systems of equations. Finally, the numerical experiment results show that the hybrid artificial fish swarm optimization algorithm owns a good globally convergent performance with a faster convergent rate. It is a new way for solving ill-conditioned linear systems of equations.
机译:基于粒子群优化(PSO)和人工鱼群算法(AFSA),提出了一种混合人工鱼类群优化算法。该新方法充分利用了PSO的快速局部收敛性能和AFSA的全球会聚性能,然后用于解决不良等式的线性系统。最后,数值实验结果表明,混合人工鱼类群优化算法拥有具有更快的收敛速率的全局融合性能。这是解决不良方程线性系统的新方法。

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