A mass assignment based ID3 algorithm for learning probabilistic fuzzy decision trees is introduced. Fuzzy partitions are used to discretise continuous feature universes and to reduce complexity when universes are discrete but with large cardinalities. Furthermore, the fuzzy partitioning of classification universes facilitates the use of these decision trees in function approximation problems. ...

This paper investigates the connection between additive fuzzy systems and kernel machines. We prove that, under quite general conditions, these two seemingly quite distinct models are essentially equivalent. As a result, algorithms based upon Support Vector (SV) learning are proposed to build fuzzy systems for classification and function approximation. The performance of the proposed algorithm ...

Through a comprehensive study of existing fuzzy neural systems, this paper presents a Choquet integral-OWA operator based fuzzy neural system named AggFNS as a new hybrid method of CI, which has advantages in universal fuzzy inference operators and importance factor expression during reasoning process. AggFNS was applied in traffic level of service evaluation problem and the experimental result...

In this paper, a neural network-driven fuzzy reasoning system for stock price forecast is proposed on the basis of improved Takagi-Sugeno reasoning model. The experimental result shows that the fuzzy neural network has such properties as fast convergence, high precision and strong function approximation ability and is suitable for real stock price prediction.

This paper considers the complementarity and equivalence relationships between convex fuzzy systems with symmetry restrictions and wavelets. Under the framework of function approximation, basic elements of fuzzy systems and wavelets theory will Author to whom all the correspondences should be addressed.

In this article we present a proposal for the descomposition of large uncertainties associated with a fuzzy set u and the multilinearization of a function f to be used in the approximation of the fuzzy set f̂(u) obtained by extension principle. Also, we present conditions on f assuring that f̂ preserves differentiability.

In this paper we embed the space of upper semicontinuous convex fuzzy sets on a Banach space into a space of continuous functions on a compact space. The following structures are preserved by the embedding: convex cone, metric, sup-semilattice. The indicator function of the unit ball is mapped to the constant function 1. Two applications are presented: strong laws of large numbers for fuzzy ran...

One of the interesting, important and attractive problems in applied mathematics is how to best approximate a function in a given space. In this paper, the problem of best approximation is considered for fuzzy functions, by optimization to obtain a fuzzy polynomial.

The shape of if-part fuzzy sets affects how well feedforward fuzzy systems approximate continuous functions. We explore a wide range of candidate if-part sets and derive supervised learning laws that tune them. Then we test how well the resulting adaptive fuzzy systems approximate a battery of test functions. No one set shape emerges as the best shape. The sinc function often does well and has ...

This paper presents a general framework for the study of fuzzy rough sets in which both constructive and axiomatic approaches are used. In constructive approach, a pair of lower and upper generalized approximation operators is defined. The connections between fuzzy relations and fuzzy rough approximation operators are examined. In axiomatic approach, various classes of fuzzy rough approximation...