The min-max composition rule and its superiority over the usual max-min composition rule

被引:23
作者
Kundu, S [1 ]
机构
[1] Louisiana State Univ, Dept Comp Sci, Baton Rouge, LA 70803 USA
关键词
fuzzy sets; equivalence relation; fuzzy inferencing;
D O I
10.1016/S0165-0114(96)00188-1
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
A close analysis of the Syllogism inference rule shows that if one uses Zadeh's notion of fuzzy if-then, then the proper way of combining the membership values of two fuzzy rules r(1): "if A, then B" and r(2): "if B, then C" is not by the usual max-min composition rule, but by the following min-max rule; tau(ij) = min {max(mu(ik), nu(kj)): all j}, where tau(ij) = m(A)(x(i)) -->m(c)(z(j)), mu(ik) = m(A)(x(i)) --> m(B)(y(k)), and v(kj) = m(B)(y(k)) --> m(c)(z(j)). The min-max value gives an upper bound on tau(ik). The min-max rule results in a new notion of transitivity and a corresponding notion of a fuzzy equivalence relation. We demonstrate the superiority of the min-max rule in terms of the properties of this equivalence relation. In particular, we argue that the new form of transitivity is particularly suitable for studying non-logical (not equal "<->") fuzzy equivalence relationships. (C) 1998 Elsevier Science B.V.
引用
收藏
页码:319 / 329
页数:11
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