Polish (Poland)English (United Kingdom)

Genetic fuzzy classifier with fuzzy rough sets for imprecise data

Type of Publication: In Book
Year: 2014
Pages: 1382–1389
Series: 2014 IEEE International Conference on Fuzzy Systems
The main problem addressed in this paper is to handle adequately imprecision of input data by means of a combination of fuzzy methods with the rough set theory. We will make use of fuzzy rough sets derived as rough approximations of fuzzy antecedent sets by non-singleton fuzzy premise sets in a fuzzy classifier. Adaptation of the parameters of this system will be done by the standard genetic algorithm.

We use cookies to improve our website and your experience when using it. Cookies used for the essential operation of the site have already been set. To find out more about the cookies we use and how to delete them, see our privacy policy.

I accept cookies from this site.