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What is Type-2 Fuzzy TOPSIS

Chapter 1
Handbook of Research on Computational Intelligence for Engineering, Science, and Business
Fuzzy TOPSIS method, a combination of ordinary TOPSIS method and Fuzzy theory, could heal some of shortcomings of uncertainties and ordinary TOPSIS in decision-making. However there are still lots of occasions in which decision-making is faced with lots of shadowiness making the Fuzzy TOPSIS method not sufficiently receptive. As a sensible response to this drawback, is to utilize a brand-new extension to TOPSIS and Fuzzy TOPSIS methods, based on type-2 fuzzy notions with ability to cope with type-2 fuzzy environment and data incorporating much more fuzziness in decision-making.
Published in Chapter:
Computational Intelligence Using Type-2 Fuzzy Logic Framework
A. Neogi (The University of Burdwan, India), A.C. Mondal (The University of Burdwan, India), and S.K. Mandal (National Institute of Technical Teachers’ Training & Research, India)
Copyright: © 2013 |Pages: 29
DOI: 10.4018/978-1-4666-2518-1.ch001
Abstract
In this chapter, the authors expand the notion of type-2 fuzzy sets. An introduction to standard and interval (type-2) fuzzy sets and systems is explained in the early part of the discussion. The chapter also covers the ideas of hybrid type-2 fuzzy system. Next, the authors study the applicability of type-2 fuzzy logic (FL) system in student’s performance in oral presentation as it is clearly new field of research topic and have an excellent opportunity to combine several fuzzy set method developed in the recent years. The proposed application shows the linkage of type-2 fuzzy system with TOPSIS. The present chapter also highlights the possible future directions for type-2 FL system research. By the end of the chapter, the authors hope that even those with little previous experience of fuzzy logic should be enabled to apply these methods in their own application areas and/or begin research in this fascinating and exciting area.
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