@inproceedings{02e1aec066c247458b243c4da39dd298,
title = "Fuzzy identification of unknown systems based on GA",
abstract = "This paper proposes a method which identifies unknown systems using fuzzy-rule based models(fuzzy models) when the input-output pairs of the system are given. It searches fuzzy models by genetic algorithms based on the given input-output pairs. The method finds all parameters of fuzzy models : the number and the position of the fuzzy sets of each input and the rule base- We encode only the fuzzy partitions of inputs into chromosomes, and then generate fuzzy rules from the encoded fuzzy partitions and the given data. We evaluate the performance with 3 functions. The experiments show that the proposed method properly locates the fuzzy sets on the input domains and generates the fuzzy rules approximating the given data.",
keywords = "Fuzzy model, Genetic algorithms, Identification, Least squares estimate",
author = "Lee, \{Jee Hyong\} and Hyung Lee-Kwang",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.; 1st Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1996 ; Conference date: 09-11-1996 Through 12-11-1996",
year = "1997",
doi = "10.1007/bfb0028538",
language = "English",
isbn = "3540633995",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "216--223",
editor = "Xin Yao and Jong-Hwan Kim and Takeshi Furuhashi",
booktitle = "Simulated Evolution and Learning - 1st Asia-Pacific Conference, SEAL 1996, Selected Papers",
}