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.
International Journal of Computational Science and Engineering, 2011 Vol.6 No.1/2, pp.132 - 140
Published online: 13 Jul 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article