Fuzzy Systems - A Tutorial - York University

Fuzzy Systems - A Tutorial by James F. Brule' (c) Copyright James F. Brule' 1985. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the copyright notice and the title and date appear, and notice is given that copying is by permission of the author. To copy otherwise, or to republish, requires a fee and/or specific permission. Introduction Fuzzy Systems is an alternative to traditional notions of set membership and logic that has its origins in ancient Greek philosophy, and applications at the leading edge of Artificial Intelligence. Yet, despite its long-standing origins, it is a relatively new field, and as such leaves much room for development. This paper will present the foundations of Fuzzy Systems , along with some of the more noteworthy objections to its use, with examples drawn from current research in the field of Artificial Intelligence.

The notion central to fuzzy systems is that truth values (in fuzzy logic) or membership values (in fuzzy sets) are indicated by a value on the range [0.0, 1.0], with 0.0 representing absolute Falseness and 1.0

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  System, Tutorials, Logic, Fuzzy logic, Fuzzy, Fuzzy systems a tutorial

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