Pattern Recognition by PSOSQP and Rule based System
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| Title | Pattern Recognition by PSOSQP and Rule based System |
| Authors | |
| Abstract | The particle swam optimization (PSO) technique is an effective global convergence method, but its local search speed is slow. The sequential quadratic programming (SQP) method can solve a nonlinear programming problem quickly, but may be trapped into a local minimum. Therefore, we combined the two individual algorithms into a new PSOSQP algorithm. Then, we applied it to find the optimal parameters of the rule based classifier. The PSOSQP rule based classifier was compared with GA, ACA, SA, and PSO, and the results prove that the proposed rule based classifier by PSOSQP is the most robust and rapid among all the algorithms. |
| Publisher | World Science Publisher |
| Date | 2012-01-26 |
| Source | 2167-633X |
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