Fuzzy inference using a least square model
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In this paper, the method of least squares is applied to the
fuzzy
inference rules. We begin studying the conditions in which from a fuzzy set
we can build another
through the method of least squares. Then we apply this technique in order
to evaluate the
conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.
fuzzy
inference rules. We begin studying the conditions in which from a fuzzy set
we can build another
through the method of least squares. Then we apply this technique in order
to evaluate the
conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.
Article Details
Com citar
Bustince Sola, Humberto Nicanor et al. «Fuzzy inference using a least square model». Mathware & soft computing, 1998, vol.VOL 5, núm. 2, http://raco.cat/index.php/Mathware/article/view/84741.
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