Fuzzy logic - A modern perspective

被引：67

作者：

Yen, J ^{[1
]}

机构：

[1] Texas A&M Univ, Dept Comp Sci, College Stn, TX 77843 USA

来源：

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 1999年 / 11卷 / 01期

基金：

美国国家科学基金会;

关键词：

fuzzy logic; artificial intelligence; approximate reasoning; possibility theory; reasoning under uncertainty; fuzzy rules; function approximation; model identification; soft computing;

D O I：

10.1109/69.755624

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traditionally, fuzzy logic (FL) has been viewed in the artificial intelligence (Al) community as an approach for managing uncertainty. In the 1990s, however, fuzzy logic has emerged as a paradigm for approximating a functional mapping. This complementary modern view about the technology offers new insights about the foundation of fuzzy logic, as well as new challenges regarding the identification of fuzzy models. In this paper, we will first review some of the major milestones in the history of developing fuzzy logic technology. After a short summary of major concepts in fuzzy logic, we discuss a modern view about the foundation of two types of fuzzy rules. Finally, we review some of the research in addressing various challenges regarding automated identification of fuzzy rule-based models.

引用

页码：153 / 165

页数：13

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