摘要
本文对微粒群优化算法(Particle Swarm Optimization)和其分类过程的智能控制进行了研究,通过调整原PSO算法中的三个重要参数,本文提出了一个模糊控制微粒群分类器(Fuzzy Controlled Particle Swarm Classifier)来改善一种已有的微粒群分类器(Particle Swarm Classifier)。在相同的数据集上,这种分类器和原有的PS分类器以及基于kNN算法的分类器进行了比较。实验结果表明,这种FCPS分类器取得了较好的结果。
A proposed particle swarm classifier has been integrated with the concept of intelligently controlling the search process of PSO to develop an efficient swarm intelligence based classifier,An intelligent fuzzy controller is designed to improve the performance and efficiency of the proposed classifier by adapting three important parameters of PSO . A data set of pattern recognition problems with different feature vector dimensions are used to demonstrate the effectiveness of the introduced classifier. The ex...
出处
《微计算机信息》
北大核心
2008年第6期254-256,共3页
Control & Automation
关键词
PS分类器
模糊控制
微粒群算法
模式识别
PS classifier
Fuzzy controller
Particle swarm optimization
Pattern recognition