Frankenstein PSO Applied to Neural Network Weights and Architectures

被引：0
|
作者：
de Lima, Natalia Flora [1 ]
Ludermir, Teresa Bernarda [1 ]
机构：
[1] Univ Fed Pernambuco, UFPE, Ctr Informat, Recife, PE, Brazil
来源：
2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年
关键词：
Particle Swarm Optimization; Neural Networks; Classification Problems; PARTICLE SWARM;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we present the FPSOA-FPSOP, a modified version of Frankstein Particle Swarm Optimization (FPSO), which is used to adjust the weights and architectures of a feed-forward neural network. To evaluate the algorithm we used benchmark classification problems in medical care area. The results were compared with other algorithms which use the same methodology to find out the weights and architectures.
引用
收藏
页码：2452 / 2456
页数：5
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