Pattern Recognition Using Particle Swarm Optimization with Proposed a New Conjugate Gradient Parameter in Unconstrained Optimization | ||
| Journal of Al-Nahrain University - Science | ||
| Article 1, Volume 19, Issue 3, September 2016, Pages 138-147 | ||
| Authors | ||
| Ban Ahmed Mitras; Suhaib Abdul-Jabbar | ||
| Abstract | ||
| In this paper, we present modified conjugancy coefficient for the conjugate gradient method. This modification using the extention Dai and Yuan Method to solve non-linear programming problems. The algorithm of particle swarm optimization (PSO) is applied in this work, to coefficients extracted by features extraction techniques. The sufficient descent and the global convergence properties for the proposed algorithm are proved. The numerical results of our finding for the large scale optimization problem are very encouraging comparison with standard methods The experimental results showed that PSO can generate excellent recognition results with the minimal set of selected features. Finally, the algorithm PSO based approaches are proposed and the influence of PSO parameters on the performance is evaluated. | ||
| Keywords | ||
| Particle swarm optimization; Pattern Recognition; conjugate gradient; conjugancy coefficient; nonlinear programming; and unconstrained optimization | ||
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