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

Author

Ma, Ming ; Zhou, Chun-Guang ; Zhang, Li-Biao ; Dou, Quan-Sheng

Author_Institution

Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China

Volume

9

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

5690

Abstract

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 networks 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.

Keywords

chemioception; fuzzy neural nets; fuzzy set theory; knowledge acquisition; particle swarm optimisation; fuzzy rule extraction; fuzzy system; near-optimal structure; network topology; taste identification; two-objective particle swarm optimization; weighted fuzzy neural network; weighting parameter; Application software; Birds; Computer science; Educational institutions; Evolutionary computation; Fuzzy neural networks; Fuzzy systems; Network topology; Neural networks; Particle swarm optimization; fuzzy neural network; fuzzy rule; particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527951

Filename

1527951