@inproceedings{f3c8252441444792b326df373a0d0d4f,
title = "A novel self-constructing evolution algorithm for TSK-type fuzzy model design",
abstract = "In this paper, a novel self-constructing evolution algorithm (SCEA) for TSK-type fuzzy model (TFM) design is proposed. The proposed SCEA method is different from the traditional genetic algorithms (GA). A chromosome of the population in GA represents a full solution and only one population presents all solutions. Our method applies a population to evaluate a partial solution locally, and several populations to construct the full solution. Thus, a chromosome represents only partial solution. The proposed SCEA uses the self-constructing learning algorithm to construct the TFM automatically that is based on the input data to decide the input partition. And we also adopted the sequence search-based dynamic evolution (SSDE) method to perform parameter learning. Simulation results have shown that the proposed SCEA method obtains better performance than some existing models.",
author = "Sheng-Fuu Lin and Chang, {Jyun Wei} and Cheng, {Yi Chang} and Hsu, {Yung Chi}",
year = "2010",
month = dec,
day = "1",
doi = "10.1109/CEC.2010.5586205",
language = "English",
isbn = "9781424469109",
series = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",
booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",
note = "null ; Conference date: 18-07-2010 Through 23-07-2010",
}