Comparative Study of Type-2 Fuzzy Sets and Cloud Model

The mathematical representation of a concept with uncertainty is one of foundations of Artificial Intelligence. Type-2 fuzzy sets study fuzziness of the membership grade to a concept. Cloud model, based on probability measure space, automatically produces random membership grades of a concept through a cloud generator. The two methods both concentrate on the essentials of uncertainty and have been applied in many fields for more than ten years. However, their mathematical foundations are quite different. The detailed comparative study will discover the relationship between each other, and provide a fundamental contribution to Artificial Intelligence with uncertainty.

[1]  Jerry M. Mendel,et al.  Type-2 fuzzy sets made simple , 2002, IEEE Trans. Fuzzy Syst..

[2]  Jerry Mendel,et al.  Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint] , 2007, IEEE Computational Intelligence Magazine.

[3]  Jerry M. Mendel The perceptual computer: an architecture for computing with words , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[4]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[5]  Jerry M. Mendel,et al.  Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters , 2000, IEEE Trans. Fuzzy Syst..

[6]  Jerry M. Mendel,et al.  Type-2 fuzzy sets and systems: an overview , 2007, IEEE Computational Intelligence Magazine.

[7]  N. N. Karnik,et al.  Introduction to type-2 fuzzy logic systems , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[8]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[9]  Song Yuan,et al.  Reliability Evaluation of Electronic Products Based on Cloud Models , 2000 .

[10]  Jerry M. Mendel,et al.  Computing with words and its relationships with fuzzistics , 2007, Inf. Sci..

[11]  Jerry M. Mendel,et al.  MPEG VBR video traffic modeling and classification using fuzzy technique , 2001, IEEE Trans. Fuzzy Syst..

[12]  LiDeyi,et al.  Study on the Universality of the Normal Cloud Model , 2005 .

[13]  Jerry M. Mendel,et al.  Aggregation Using the Fuzzy Weighted Average as Computed by the Karnik–Mendel Algorithms , 2008, IEEE Transactions on Fuzzy Systems.

[14]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[15]  Jerry M. Mendel,et al.  Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 1, Forward Problems , 2006, IEEE Transactions on Fuzzy Systems.