I. AIM AND SCOPE<br>Type–2 fuzzy sets and systems have emerged during the past decade as major areas within the general field of fuzzy sets and systems. This is because they are a natural next step in the progression of general research about fuzzy sets and systems and because many applications that use type–2 fuzzy sets have already demonstrated significant performance improvements over using type–1 fuzzy sets.<br>During the past decade most of the work that used type–2 fuzzy sets and systems focused on the simplest kinds of such sets and system, namely interval type–2 fuzzy sets (also known as interval–valued fuzzy sets) and interval type–2 fuzzy logic systems. Recently, however, important advances have been made in the theory of general type–2 fuzzy sets and systems. Type–2 fuzzy sets also are important for computing with words, because words mean different things to different people and such linguistic uncertainty can be modeled using type–2 fuzzy sets.<br>The aim of this special issue is to highlight the most significant recent developments – advances – on the topics of type–2 fuzzy sets and systems, to identify the most recent research directions, and to publicize this area to a wider audience.<br>II. TOPICS COVERED<br>Authors are invited to submit their original and unpublished work in the areas including (but not limited to) the following (note that "type–2" includes interval type–2/interval–valued and general type–2):<br>– Theoretical studies of current type–2 paradigms and algorithms<br>– evelopments of new type–2 paradigms and algorithms<br>– Convincing applications of type–2 fuzzy logic<br>– Type–2 fuzzy logic control<br>– Type–2 classification/clustering<br>– Type–2 for computing with words<br>– Quantitative comparisons of type–2 and type–1 fuzzy systems<br>– Type–2 uncertainty measures<br>– Optimization under type–2 constraints<br>– Optimization of Type–2 fuzzy systems<br>– Learning type–2 fuzzy systems<br>– Adaptive type–2 fuzzy systems<br>
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