Improved particle swarm optimization algorithms for electromagnetic optimization

被引：5
|
作者：
Mussetta, Marco [1 ]
Selleri, Stefano [2 ]
Pirinoli, Paola [3 ]
Zich, Riccardo E. [1 ]
Matekovits, Ladislau [3 ]
机构：
[1] Politecn Milan, DEE, I-20133 Milan, Italy
[2] Univ Florence, DET, I-50134 Florence, Italy
[3] Politecn Torino, DEE, I-10129 Turin, Italy
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2008年 / 19卷 / 01期
关键词：
genetic algorithm; particle swarm; optimization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Particle Swarm is a relatively novel approach for global stochastic optimization. In this paper some variations over the basic algorithm are proposed, with the aim of a more efficient search over the solution space obtained with a negligible overhead in both complexity and speed. The presented algorithms are then applied to a mathematical test function and to a microwave microstrip filter to show their superior capabilities with respect to the conventional version.
引用
收藏
页码：75 / 84
页数：10
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