PROBABILITIES, POSSIBILITIES, AND FUZZY-SETS

被引：22

作者：

DRAKOPOULOS, JA

机构：

[1] Department of Computer Science, Knowledge Systems Laboratory, Stanford University, Palo Alto, CA 94304-0106

来源：

FUZZY SETS AND SYSTEMS | 1995年 / 75卷 / 01期

基金：

美国国家航空航天局;

关键词：

PROBABILITY; POSSIBILITY; FUZZY SETS; ARTIFICIAL INTELLIGENCE; UNCERTAINTY; MEASURE AND SET THEORY; RELATIONS;

D O I：

10.1016/0165-0114(94)00341-4

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A formal analysis of probabilities, possibilities, and fuzzy sets is presented in this paper. A number of theorems proved show the above measures have equal representational power when their domains are infinite. However, for finite domains, it is proved that probabilities have a higher representational power than both possibilities and fuzzy sets. The cost of this increased power is high computational complexity and reduced computational efficiency. The resulting trade-off of high complexity and representational power versus computational efficiency is discussed under the spectrum of experimental systems and applications.

引用

页码：1 / 15

页数：15

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