Query Optimization Based on the Simulated Annealing and Particle Swarm Optimization

Abstract:

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In order to allow the user to quickly and accurately search the required information, a query optimization method based on a simulated annealing and particle swarm hybrid algorithm is proposed. The basic idea is: the query population into two flat sub populations, a sub population by using simulated annealing algorithm optimization, another sub populations by using particle swarm algorithm optimization, comparison of two adaptive values, to find the global optimal value. The experimental results show that the mixed algorithm, can further improve the precision and recall of query optimization.

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Periodical:

Edited by:

Mohamed Othman

Pages:

1870-1873

Citation:

R. J. Song and Y. Wang, "Query Optimization Based on the Simulated Annealing and Particle Swarm Optimization", Applied Mechanics and Materials, Vols. 229-231, pp. 1870-1873, 2012

Online since:

November 2012

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$38.00

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