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IEEE Computational Intelligence Magazine

Issue 1 • Date Feb. 2007

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Displaying Results 1 - 18 of 18
  • Front cover - IEEE Computational Intelligence Magazine - Feb. 2007

    Publication Year: 2007, Page(s): c1
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  • IEEE Computational Intelligence Magazine

    Publication Year: 2007, Page(s): 1
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  • Better is Yet to Come [Editor's Remarks]

    Publication Year: 2007, Page(s): 2
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  • Educational Activities [President's Message]

    Publication Year: 2007, Page(s):3 - 4
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  • Modelling and Prediction of the MXNUSD Exchange Rate Using Interval Singleton Type-2 Fuzzy Logic Systems [Application Notes]

    Publication Year: 2007, Page(s):5 - 8
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (417 KB) | HTML iconHTML

    An IT2 SFLS using hybrid RLS-BP training method was tested and compared for forecasting the daily exchange rate between Mexican Peso and U.S. Dollar (MXNUSD). The results showed that the IT2 SFLS forecaster using RLS-BP hybrid learning provided the best performance, and the base line T1 SFLS provided the worst performance. We conclude, therefore, that it is possible to directly use the daily data ... View full abstract»

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  • What is Where? Type-2 Fuzzy Sets for Geographical Information [Research Frontier]

    Publication Year: 2007, Page(s):9 - 14
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3827 KB) | HTML iconHTML

    Until recently, most research has been done on type-1 fuzzy sets but it is also possible to identify and model type-2 fuzzy sets, and possibly type-n fuzzy sets. Until recently, the question of type-n fuzzy sets has not emerged in the consideration of spatial fuzzy sets. In this short summary, I will present some recent research that has explored the generation of type-2 spatial fuzzy sets, and di... View full abstract»

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  • Society Briefs

    Publication Year: 2007, Page(s):15 - 18
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  • Third International Seminar on Computational Intelligence 2006, IEEE CIS Mexico Chapter [Family Corner]

    Publication Year: 2007, Page(s): 19
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  • Type-2 fuzzy sets and systems: an overview

    Publication Year: 2007, Page(s):20 - 29
    Cited by:  Papers (152)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1228 KB)

    This paper provides an introduction to and an overview of type-2 fuzzy sets (T2 FS) and systems. It does this by answering the following questions: What is a T2 FS and how is it different from a T1 FS? Is there new terminology for a T2 FS? Are there important representations of a T2 FS and, if so, why are they important? How and why are T2 FSs used in a rule-based system? What are the detailed com... View full abstract»

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  • Type-2 FLCs: A New Generation of Fuzzy Controllers

    Publication Year: 2007, Page(s):30 - 43
    Cited by:  Papers (117)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3109 KB) | HTML iconHTML

    Type-1 fuzzy logic controllers (FLCs) have been applied to date with great success to many different applications. However, for dynamic unstructured environments and many real-world applications, there is a need to cope with large amounts of uncertainties. The traditional type-1 FLC using crisp type-1 fuzzy sets cannot directly handle such uncertainties. A type-2 FLC using type-2 fuzzy sets can ha... View full abstract»

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  • Uncertain Fuzzy Clustering: Insights and Recommendations

    Publication Year: 2007, Page(s):44 - 56
    Cited by:  Papers (18)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1663 KB) | HTML iconHTML

    In this article, interval type-2 fuzzy sets were used to model the uncertainty that is associated with the various parameters in objective function-based clustering. The purpose was to represent and manage the uncertainty in the cluster memberships by incorporating interval type-2 fuzzy sets. As a result, interval type-2 clustering methods were obtained by modifying the prototype-updating and hard... View full abstract»

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  • Type-2 Fuzzy Logic: A Historical View

    Publication Year: 2007, Page(s):57 - 62
    Cited by:  Papers (54)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (981 KB) | HTML iconHTML

    Type-2 fuzzy logic offers an opportunity to model levels of uncertainty with which traditional fuzzy logic (type-1) struggles. This article provides a historical perspective of the development of type-2 fuzzy logic with a retrospective review of important developments in the field. We discuss key questions about the technology such as - when should type-2 systems be used? and why has it taken so l... View full abstract»

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  • Implementing Interval Type-2 Fuzzy Processors [Developmental Tools]

    Publication Year: 2007, Page(s):63 - 71
    Cited by:  Papers (23)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (809 KB) | HTML iconHTML

    This article discusses some relevant methodological aspects for implementing IT2-FLS on hardware. First it describes a hardware architecture for an IT2-FP. In addition, it details particular considerations for the design of the different components of the architecture. As a study case, a simple implementation of an IT2-FP in FPGA technology is presented View full abstract»

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  • Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions (Mendel, J.M.; 2001) [book review]

    Publication Year: 2007, Page(s):72 - 73
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  • In Memoriam: George Nikolaos Saridis (November 17, 1931-October 29, 2006)

    Publication Year: 2007, Page(s):74 - 75
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  • Conference Calendar

    Publication Year: 2007, Page(s): 76
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  • Paper Submission Guidelines and Information for authors

    Publication Year: 2007, Page(s):77 - 78
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  • Call for Papers: IEEE Transactions on Fuzzy Systems

    Publication Year: 2007, Page(s): 79
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Aims & Scope

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications, in keeping with the Field of Interest of the IEEE Computational Intelligence Society (IEEE/CIS). 

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