Abstract
Based on particle swarm optimization (PSO) and artificial fish swarm algorithm (AFSA), this paper proposes a hybrid artificial fish swarm algorithm (HAFSA). The method makes full use of the fast local convergence performance of PSO and the global convergence performance of AFSA, and then is used for solving ill-conditioned linear systems of equations. Finally, the numerical experiment results show that hybrid artificial fish swarm algorithm owns a better global convergence performance with a faster convergence rate. It is a new way to solve ill-conditioned linear systems of equations.
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Zhou, Y., Huang, H., Zhang, J. (2011). Hybrid Artificial Fish Swarm Algorithm for Solving Ill-Conditioned Linear Systems of Equations. In: Chen, R. (eds) Intelligent Computing and Information Science. ICICIS 2011. Communications in Computer and Information Science, vol 134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18129-0_99
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DOI: https://doi.org/10.1007/978-3-642-18129-0_99
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18128-3
Online ISBN: 978-3-642-18129-0
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