A Review of Particle Swarm Optimization: Feature Selection, Classification and Hybridizations
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Abstract
Particle swarm optimization (PSO) is a recently grown, popular, evolutionary and conceptually simple but efficient algorithm which belongs to swarm intelligence category. This paper outlines basic concepts and reviews PSO based techniques with their applications to classification and feature selection along with some of the hybridized applications of PSO with similar other techniques.
DOI: 10.17762/ijritcc2321-8169.160418
DOI: 10.17762/ijritcc2321-8169.160418
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How to Cite
, M. M. S. A. S. L. K. G. (2015). A Review of Particle Swarm Optimization: Feature Selection, Classification and Hybridizations. International Journal on Recent and Innovation Trends in Computing and Communication, 3(4), 1816–1820. https://doi.org/10.17762/ijritcc.v3i4.4134
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