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Soft Computing and Its Applications, Volume One
book

Soft Computing and Its Applications, Volume One

by Kumar S. Ray
September 2014
Intermediate to advanced
632 pages
21h 5m
English
Apple Academic Press
Content preview from Soft Computing and Its Applications, Volume One
Fuzzy Logic 233
sufficient because each fuzzy truth-value represents a fuzzy subset rather than
a single element of [0,1]. Thus, we gain by trading the large number of simple
Łukasiewicz truth-values for the small number of less simple truth-values of
fuzzy logic.
The method of approximate reasoning essentially deals with propositions which
are fuzzy rather than precise, e.gFor example., “weather is very hot’’, “he is
looking very beautiful’’, “soup is not very tasty’’, and so on. etc.
Clearly, the fuzzy truth-values of fuzzy logic are more commensurate with the
fuzziness of such propositions than the numerical Łukasiewicz truth-values.
3.4.4 OPERATIONS ON FUZZY TRUTH VALUES
So far we have discussed the structure of the truth value set of fuzzy ...
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Publisher Resources

ISBN: 9781926895383