Fuzzy rule extraction by two-objective particle particle swarm optimization and application for taste identification of tea

被引：0
|
作者：
Ma, M [1 ]
Zhou, CG [1 ]
Zhang, LB [1 ]
Dou, QS [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
来源：
PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年
关键词：
fuzzy rule; particle swarm optimization; fuzzy neural network;
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：
The extraction of fuzzy rules is always a difficult problem to fuzzy system, in this problem performance and complexity are two conflicting criteria. We have proposed a two-objective algorithm based on particle swarm optimization algorithm and the weighted fuzzy neural network. It can evolve both the fuzzy neural network's topology and weighting parameters and obtained the near-optimal structure of fuzzy neural network for taste identification of tea. Numerical simulations show the effectiveness of the proposed algorithm.
引用
收藏
页码：5690 / 5694
页数：5
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