Title :
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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527951
