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Issue No.01 - January/February (1999 vol.11)
pp: 153-165
ABSTRACT
<p><b>Abstract</b>—Traditionally, fuzzy logic (FL) has been viewed in the artificial intelligence (AI) 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.</p>
INDEX TERMS
Fuzzy logic, artificial intelligence, approximate reasoning, possibility theory, reasoning under uncertainty, fuzzy rules, function approximation, model identification, soft computing.
CITATION
John Yen, "Fuzzy Logic-A Modern Perspective", IEEE Transactions on Knowledge & Data Engineering, vol.11, no. 1, pp. 153-165, January/February 1999, doi:10.1109/69.755624
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