A novel particle swarm algorithm for solving parameter identification problems on graphics hardware. (14th July 2011)

• Record Type: Journal Article
• Authors: Wang, Jing; Wu, Zhijian; Wang, Hui
• Is Part Of: International journal of computational science and engineering. Volume 6:Number 1/2(2011)
• Page Start: 43
• Page End: 51
• Publication Date: 2011-07-14
• Subjects: particle swarm optimisation -- PSO -- graphics hardware -- opposition-based learning -- OBL -- parameter identification -- inverse problem -- parallel computing; Computer science -- Mathematics -- Periodicals; Computer simulation -- Mathematical aspects -- Periodicals; Computational intelligence -- Periodicals; 004.015105
• Languages: English
• ISSNs: 1742-7185

Abstract

This paper presents a fine-grained novel particle swarm optimisation (PSO) algorithm on graphics hardware. It has good performance on a collection of parameter identification problems. In this algorithm, a generalised opposition-based learning (GOBL) strategy is embedded into PSO algorithm. This strategy can transform the current solution space to provide more chances of finding better solutions, and the parallel computing on graphics hardware can accelerate the convergence rate significantly. Experiment results show that the novel algorithm on graphics hardware has not only a good tolerability with the noise in the observed data but also a very high speedup.