Recent Advancement in Fuzzy System: Full Type 2 Fuzziness

Recent Advancement in Fuzzy System: Full Type 2 Fuzziness

İ. Burhan Türkşen (TOBB-ETU, Turkey & University of Toronto, Canada) and İbrahim Özkan (Hacettepe University, Turkey & University of Toronto, Canada)
Copyright: © 2014 |Pages: 11
DOI: 10.4018/978-1-4666-6070-0.ch010
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Abstract

Decision under uncertainty is an active interdisciplinary research field. A decision process is generally identified as the action of choosing an alternative that best suites our needs. This process generally includes several areas of research including but not limited to Economics, Psychology, Philosophy, Mathematics, Statistics, etc. In this chapter the authors attempt to create a framework for uncertainties which surrounds the environment where human decision making takes place. For this purpose, the authors discuss how one ought to handle uncertainties within Fuzzy Logic. Furthermore, they present recent advances in Type 2 fuzzy system studies.
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Uncertainty

At the beginning, more often one starts with a dictionary definition of uncertainty. Uncertainty is commonly referred to “the state of being uncertain.” Not known, not definite, not sure of something, not precise, fuzzy, vague, contradictory, etc. are among several meanings of the term “uncertain.” Think about the precision of some words, for example, “about,” “approximately,” “roughly,” “low,” “high” and “big.” They have no precise meanings although they are used frequently in daily life. Humans do understand them and communicate effectively using them. According to Parsons (2001), the meaning of the word “uncertain” falls into three categories. Something is uncertain because; (1) it hasn’t been measured accurately enough, (2) because it might change and (3) the person who has the information is not confident.

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