Abstract
Alternative approaches to data processing, e.g., fuzzy set theory, rough set theory and neural networks, known collectively as ‘soft computing,’ have drawn significant interest from the scientific community. They have already found numerous applications to real-world problems and will certainly become even more important in the future. This paper concentrates on two important classes of soft computing methods, i.e., fuzzy sets and rough sets. In particular, knowledge acquisition and representation in fuzzy and rough controllers is discussed and compared. The paper is concluded with an illustrative example, showing the application of fuzzy and rough set theory to the control of the ‘inverted pendulum.’
Get full access to this article
View all access options for this article.