Probabilistic-constrained Fuzzy Logic for Situation Modeling

被引：0

作者：

Xiong, Jinhua ^{[1
]}

Fan, Jianping ^{[2
]}

机构：

[1] Chinese Acad Sci, Inst Comp Technol, Beijing 100191, Peoples R China

[2] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3 | 2009年

关键词：

D O I：

10.1109/FUZZY.2009.5277232

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

How to model situation user-friendly and precisely is a key issue for situation-aware applications. Fuzzy logic is an effective approach to model situation, but one obstacle is how to select the suitable operators between different fuzzy sets. One possibility is to combine the merit of both Fuzzy logic and Probability logic. The paper first introduces a set of constraints on conventional fuzzy logic and its operations, to setup a unified framework so as to combine the merits of the above two approaches. Such probabilistic-constrained fuzzy logic can be used in situation-aware applications. The paper then focuses on how to derive new fuzzy concepts from basic rum, partition, and how to compute the relationship between such derived and basic fuzz), concepts according to the probability constraints, which is different from the conventional ones.

引用

页码：860 / +

页数：2

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