Nonlinear context adaptation in the calibration of fuzzy sets

✍ Scribed by W. Pedrycz; R.R. Gudwin; F.A.C. Gomide

• Publisher: Elsevier Science
• Year: 1997
• Tongue: English
• Weight: 404 KB
• Volume: 88
• Category: Article
• ISSN: 0165-0114
• DOI: 10.1016/s0165-0114(96)00057-7

✦ Synopsis

In this note we elaborate on the concept and use of context adaptation. The underlying idea hinges upon a nonlinear transformation of an actual reference unit universe of discourse into a subset of reals, say [a, b], that is implied by actually available data (current context). Assuming a collection of fuzzy sets ,~ --{A1, A2 ..... A,,} defined over [0, 1], the context adaptation gives rise to a new frame of cognition ~_/' ' ' ' {AL, A 2 .... ,An} expressed over [a,b]. Owing to the inherent nonlinearity of the developed mapping, different elements (fuzzy sets) of ,4 can be "stretched" or "expanded" according to the given experimental data. Proposed is a neural network as a relevant optimization tool. @1997 Elsevier Science B.V.