An overview of fuzzy quantifiers. (II). Reasoning and applications

被引:1
|
作者
Liu, YX
Kerre, EE
机构
[1] Beijing Univ, Dept Comp Sci & Technol, Artificial Intelligence Lab, Beijing 100871, Peoples R China
[2] Univ Ghent, Dept Appl Math & Comp Sci, Fuzziness & Uncertainty Modelling Res Unit, B-9000 Ghent, Belgium
关键词
fuzzy logic; approximate reasoning; fuzzy quantifier; possibility; usuality; belief theory; quantifier extension principle; interval-valued quantifier; fuzzy decision making; fuzzy database systems;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In the second part of the overview, reasoning with fuzzily defined quantifiers and applications are presented, Possibility based reasoning is summarized in detail. The widely used quantifier extension principle and various reasoning schemas derived from it are discussed. Some disadvantages of the quantifier extension principle are pointed out. Although interval-valued quantifiers are only a special case of general quantifiers, some specific properties and results arise from them. Furthermore, they suggest another approach to inference with fuzzy quantifiers. Reasoning with quantification and several kinds of qualification is introduced. This kind of reasoning requires a seamless synthesis of probability theory, possibility theory, fuzzy logic and belief theory. At last, the applications of fuzzily defined quantifiers in decision making and fuzzy database systems are introduced. (C) 1998 Published by Elsevier Science B.V.
引用
收藏
页码:135 / 146
页数:12
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