@inproceedings{8ea4b36594a84e878b91ad9dfce9602c,
title = "Genetic fuzzy logic controllers",
abstract = "The conventional fuzzy logic controller (CFLC) Is limited In application, because its logic rules and membership functions have to be preset with expert knowledge. To avoid such drawbacks, a genetic fuzzy logic controller (GFLC) is proposed by employing an Iterative evolution algorithm to promote the learning performance of logic rules and the tuning effectiveness or membership functions from examples in sequence. In addition, an encoding method is developed to overcome the difficulties in dealing with numerous constraints while employing genetic algorithms in tuning membership functions. A case of GM car-following behavior is experimented to verify the applicability and robustness of GFLC. The results demonstrate that GFLC can predict the car-following behaviors precisely. Due to the similarity between fuzzy neural networks (FNN) and GFLC, a comparison is also made and the results indicate that GFLC performs superior to FNN.",
keywords = "Ear-following behaviors, Fuzzy logic controller, Fuzzy neural network, Genetic algorithms, Genetic fuzzy logic controller",
author = "Yu-Chiun Chiou and Lan, {Lawrence W.}",
year = "2002",
month = jan,
day = "1",
doi = "10.1109/ITSC.2002.1041214",
language = "English",
series = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "200--205",
editor = "Der-Horng Lee and Dipti Srinivasan and Cheu, {Ruey Long}",
booktitle = "IEEE 5th International Conference on Intelligent Transportation Systems, ITSC 2002 - Proceedings",
address = "美國",
note = "5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002 ; Conference date: 03-09-2002 Through 06-09-2002",
}