A Rough-set-based for fuzzy modeling with outlier

For high nonlinearly or unknown systems, the interest is toward data-driven methods for obtaining the system model. Fuzzy-rule-based modeling is a suitable tool that combines good approximation properties with a certain degree of inspects ability. The rough set theory is successes to deal with imprecise, incomplete or uncertain for information system. Fuzzy set and the rough set theories turned out to be particularly adequate for the analysis of various types of data, especially, when dealing with inexact, uncertain or vague knowledge. In this paper, we propose an novel algorithm, which termed as rough-based fuzzy C-regression model (RFCRM), that define fuzzy subspaces in a fuzzy regression manner and also include rough-set theory for TSK modeling with robust capability against outliers.