Welcome to the Journal of Intelligent and Fuzzy Systems’s special issue for “FUZZYSS’2009: 1st International Fuzzy Systems Symposium”. Since its introduction by Prof. Lotfi A. Zadeh fuzzy logic has found numerous applications in many diverse areas. Scientific research related to fuzzy logic and its extensions is still an open and promising active research area. There is still a very long way to go and much to explore. It is now very well known by researchers and practitioners that fuzzy logic and systems provides a lot of tools and methodologies to model uncertainty and ambiguity which is an important characteristics of many real life systems. However, we should mention here that in most of the cases it is not straightforward to distinguish between problems that actually require a crisp or fuzzy approach in their modeling and solution. Actually, the boundary between them is also uncertain. What types of problems really require modeling and solution through fuzzy logic? What is “fuzziness” in them? This is actually the first fundamental question which needs to be answered before developing a successful fuzzy model and solution methodology with fuzzy logic approaches. In this special issue the readers will find some of the innovative applications of fuzzy sets and systems to several interesting problems. The special issue provides good quality original research papers that were presented orally and discussed at the “FUZZYSS’2009: 1st International Fuzzy Systems Symposium, 1–2 October 2009, Ankara, Turkey”, some of which were selected as candidates
[1]
Nevin Güler,et al.
An improved Takagi-Sugeno fuzzy model with multidimensional fuzzy sets
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2010,
J. Intell. Fuzzy Syst..
[2]
Ziya Telatar,et al.
Fuzzy logic based four-voice choral harmonization in traditional style
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2010,
J. Intell. Fuzzy Syst..
[3]
Vesa A. Niskanen,et al.
Application of approximate reasoning to hypothesis verification
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2010,
J. Intell. Fuzzy Syst..
[4]
Türkay Dereli,et al.
Application of possibilistic fuzzy regression for technology watch
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2010,
J. Intell. Fuzzy Syst..
[5]
Lale Özbakir,et al.
Balancing fuzzy multi-objective two-sided assembly lines via Bees Algorithm
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2010,
J. Intell. Fuzzy Syst..
[6]
Inci Batmaz,et al.
Classification models based on Tanaka's fuzzy linear regression approach: The case of customer satisfaction modeling
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2010,
J. Intell. Fuzzy Syst..
[7]
Rifat Gürcan Özdemir,et al.
Multi objective new product development in bakery production under fuzzy demand parameters
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2010,
J. Intell. Fuzzy Syst..