Principal components analysis by the galaxy-based search algorithm: a novel metaheuristic for continuous optimisation Online publication date: Wed, 18-Mar-2015
by Hamed Shah-Hosseini
International Journal of Computational Science and Engineering (IJCSE), Vol. 6, No. 1/2, 2011
Abstract: In this paper, the principal components analysis (PCA) is formulated as a continuous optimisation problem. Then, a novel metaheuristic inspired from nature is employed to explore the search space for the optimum solution to the PCA problem. The new metaheuristic is called 'galaxy-based search algorithm' or 'GbSA'. The GbSA imitates the spiral arm of spiral galaxies to search its surrounding. This spiral movement is enhanced by chaos to escape from local optimums. A local search algorithm is also utilised to adjust the solution obtained by the spiral movement of the GbSA. Experimental results demonstrate that the proposed GbSA for the PCA or GbSA-PCA is a promising tool for the PCA estimation.
Online publication date: Wed, 18-Mar-2015
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