Title :
A Hybrid Scheme for the Function Optimization
Author :
Ailing, Chen ; Xitang, Zhang
Author_Institution :
Sch. of Inf. Manage., Shandong Economic Univ., Ji´´nan, China
Abstract :
To improve the precision of the function prediction, an effective optimization approach is proposed, where genetic algorithm (GA) and self-adaptive particle swarm optimization algorithm are hybridized to enhance the searching ability. Simulation results have shown that the hybrid scheme is effective and efficient for the function prediction.
Keywords :
genetic algorithms; particle swarm optimisation; search problems; function optimization; function prediction; genetic algorithm; hybrid scheme; searching ability; self-adaptive particle swarm optimization; Algorithm design and analysis; Gallium; Optimization; Particle swarm optimization; Simulation; Strontium; function pridiction; genetic algorithm; hybrid scheme; particle swarm optimization;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.296
