Acquisition of pattern classification rule based on particle swarm optimization

被引：0

作者：

Gao, Liang ^{[1
]}

Gao, Haibing ^{[1
]}

Zhou, Chi ^{[1
]}

Yu, Daoyuan ^{[1
]}

机构：

[1] Dept. of Industrial Eng., Huazhong Univ. of Sci. and Technol., Wuhan 430074, China

来源：

Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2004年 / 32卷 / 11期

关键词：

Computer simulation - Fuzzy sets - Intelligent control - Numerical methods - Optimization;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper presented a rule extraction algorithm based on particle swarm optimization. A single rule was encoded as a particle; through its velocity-position search model and the information stored by the particles, the optimal classification rule set was generated. The proposed algorithm was used to generate pattern classification rules for Iris data set. The simulation results showed that the classification rules generated by the proposed algorithm achieved more classification accuracy and lower computational cost than the other methods.

引用

页码：24 / 26

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