WASET
	%0 Journal Article
	%A Ahcene Habbi and  Yassine Boudouaoui
	%D 2014
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 96, 2014
	%T Hybrid Artificial Bee Colony and Least Squares Method for Rule-Based Systems Learning
	%U https://publications.waset.org/pdf/9999914
	%V 96
	%X This paper deals with the problem of automatic rule
generation for fuzzy systems design. The proposed approach is based
on hybrid artificial bee colony (ABC) optimization and weighted least
squares (LS) method and aims to find the structure and parameters of
fuzzy systems simultaneously. More precisely, two ABC based fuzzy
modeling strategies are presented and compared. The first strategy
uses global optimization to learn fuzzy models, the second one
hybridizes ABC and weighted least squares estimate method. The
performances of the proposed ABC and ABC-LS fuzzy modeling
strategies are evaluated on complex modeling problems and compared
to other advanced modeling methods.

	%P 2155 - 2158