In this paper, we present an algorithm to infer a fuzzy partition over a set of numerical values. This algorithm is based on the mathematical morphology and is expressed in the formal language theory. We use it during the construction of a fuzzy decision tree, in the case where no fuzzy partition is available for a numerical attribute. R esum e Dans ce rapport, nous pr esentons un algorithme po...

We examine gauge theories on Minkowski space-time times fuzzy coset spaces. This means that the extra space dimensions instead of being a continuous coset space S/R are a corresponding finite matrix approximation. The gauge theory defined on this non-commutative setup is reduced to four dimensions and the rules of the corresponding dimensional reduction are established. We investigate in partic...

In this paper, the Henstock integral for fuzzy-number-valued functions in R is defined and some properties of this integral are discussed. Finally, by using the embedding theorem the fuzzy number space E can be embedded into a concrete space, some characterized theorems for this integral are given. AMS Subject Classification: 94D05, 46S40, 47S40, 54A40

This paper presents the application of fuzzy set theory (FST) within the context of integrated planning and scheduling. Fuzzy set theory provides a framework for modelling uncertain or ambiguous information, which is commonly encountered in industry. A typical example of a r l i a p e t s d p c s ©

|||||||||||||||||||||||||||||||Abstract In this paper, the researcher proposes a modi ed new method to rank L-R fuzzy numbers. The modi ed method uses a defuzzi cation of parametrically represented fuzzy numbers that have been studied in [20]. This parameterized defuzzi cation can be used as a crisp approximation with respect to a fuzzy quantity. In this article, the researcher uses this defuzz...

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. Cheng (Cheng, C. H. (1998). A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets and Systems, 95, 307–317) pointed out that the proof of the statement ‘‘Ranking of generalized fuzzy numbers does not depe...

The management of uncertainty and imprecision is becoming more and more important in knowledge-based systems. Fuzzy logic provides a systematic basis for representing and inferring with this kind of knowledge. This paper describes an approach for fuzzy inference based on an uncertainty forward propagation method and a change in the granularity of the elements involved. The proposed model is abl...

[1] K. J. Hunt, R. Hass, and R. Murray-Smith, “Extending the functional equivalence of radial basis function networks and fuzzy inference systems,” IEEE Trans. Neural Networks, vol. 7, pp. 776–781, May 1996. [2] J.-S. R. Jang, C.-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, MATLAB Curriculum Series. Upper Saddle River, N...