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Fuzzy Logic Tutorial Part II:
LINGUISTIC
VARIABLES
By
Vadiraj Joshi |
These are the important terms in fuzzy logic because it
involves its main features. A linguistic variable allows us to describe
its value qualitatively and quantitatively:
- Qualitatively:
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With a linguistic term.
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Serving as the name of a fuzzy set, regarding the
example we saw above it was TALL
- Quantitatively:
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With a number
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Very useful to process numeric input data
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Regarding Fuzzy Logic it was the
membership function (which expresses the meaning of the fuzzy set, its
belonging
Fuzzy logic combines these two aspects of variables
into a uniform framework. This is very useful because the qualitatively
description is very understandable for us, and the quantitatively
description is very useful to compute data and get output values.
A fuzzy set has this dual representation, a linguistic
term and a numeric value through its membership function, which maps
elements in a universe of discourse (i.e. all the different heights) to
their membership degree in the set. Above mentioned all are summarized
into following figure 3.
Figure 3: Fuzzy Set and Membership Function
Section 3 is about fuzzy sets in detail. |
