Title: Principal components analysis by the galaxy-based search algorithm: a novel metaheuristic for continuous optimisation

Authors: Hamed Shah-Hosseini

Addresses: Faculty of Electrical and Computer Engineering, Shahid Beheshti University, G.C., Tehran, Iran

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.

Keywords: principal components analysis; PCA; metaheuristics; optimisation; chaos; galaxy based search; spiral arm; spiral galaxies.

DOI: 10.1504/IJCSE.2011.041221

International Journal of Computational Science and Engineering, 2011 Vol.6 No.1/2, pp.132 - 140

Published online: 18 Mar 2015 *

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