@inproceedings{c4d17e9a3979487e98d5cdc35196a017,
title = "Group-based evolutionary swarm intelligence for recurrent fuzzy controller design",
abstract = "Recurrent fuzzy controller design by the hybrid of Multi-group Genetic Algorithm and Particle Swarm Optimization (R-MGAPSO), is proposed in this paper. The recurrent fuzzy controller designed here is the Takagi-Sugeno-Kang (TSK)-type Recurrent Fuzzy Network (TRFN). Both the number of fuzzy rules and parameters in TRFN are designed concurrently by R-MGAPSO. Evolution of population consists of three major operations: group enhancement by particle swarm optimization, variable-length individual crossover and mutation. To verify the performance of R-MGAPSO, control of a dynamic plant is simulated and compared with other genetic algorithms",
author = "Juang, {Chia Feng} and Chung, {I. Fang} and Chen, {Shin Kuan}",
year = "2006",
doi = "10.1109/FUZZY.2006.1681936",
language = "English",
isbn = "0780394887",
series = "IEEE International Conference on Fuzzy Systems",
pages = "1710--1714",
booktitle = "2006 IEEE International Conference on Fuzzy Systems",
note = "null ; Conference date: 16-07-2006 Through 21-07-2006",
}