Special session on fuzzy and rough hybridization and applications

Fuzzy sets and rough sets are both well-established mathematical models for representing and processing imperfect information. It was recognized early on that they are complementary, rather than competitive; a first hybrid fuzzy rough set model was proposed in 1990. Recently, interest in hybrid fuzzy and rough models really started booming, when their potential in machine learning (especially data reduction) was successfully demonstrated. These applications raise new challenges for the hybrid theory, and at the same time, new theoretical developments in rough set theory and fuzzy set theory open up alternative ways to combine both models.

The aim of this special session is to bring together researchers and practitioners from both fields to present and discuss emerging developments in the hybridization of fuzzy and rough sets.

Organizers: Chris Cornelis, University of Granada, Spain
Richard Jensen, University of Aberystwyth, United Kingdom
Neil Mac Parthalain, University of Aberystwyth, United Kingdom
Wei-Zhi Wu, Zhejian Ocean University, P.R. China