The classification and regression trees (CART) possess the advantage of being able to handlelarge data sets and yield readily interpretable models. In spite to these advantages, they are alsorecognized as highly unstable classifiers with respect to minor perturbations in the training data.In the other words methods present high variance. Fuzzy logic brings in an improvement in theseaspects due ...

Seismic hazard assessment like many other issues in seismology is a complicated problem, which is due to a variety of parameters affecting the occurrence of an earthquake. Uncertainty, which is a result of vagueness and incompleteness of the data, should be considered in a rational way. Using fuzzy method makes it possible to allow for uncertainties to be considered. Fuzzy inference system,...

Fuzzification of support vector machine has been utilized to deal with outlier and noise problem. This importance is achieved, by the means of fuzzy membership function, which is generally built based on the distance of the points to the class centroid. The focus of this research is twofold. Firstly, by taking the advantage of robust statistics in the fuzzy SVM, more emphasis on reducing the im...

In last years, a variety of papers on fuzzy sets and other fuzzy topics was concerned with set-algebraic operations for and properties of fuzzy sets. However, only few remarks are devoted to fuzzy cardinals. In classical set theory the cardinality of a set is a measure of its size or "power". In the fuzzy case one has to differentiate: there are measures of fuzziness and measures of power. Here...

In this paper we use concepts from the lattice-based theory of morphological operators and fuzzy sets to develop generalized lattice image operators that can be expressed as nonlinear convolutions that are suprema or infima of fuzzy intersection or union norms. Our emphasis (and differences with previous works) is the construction of pairs of fuzzy dilation and erosion operators that form latti...

Fuzzy control can be interpreted as an approximation technique for a control function based on typical, imprecisely speciied input{output tuples that are represented by fuzzy sets. The imprecision is characterized by similarity relations that are induced by transformations of the canonical distance function between real numbers. Taking this interpretation of fuzzy controllers into account, in o...

In image processing, image segmentation is one of the important tasks to extract information from the images. A variety of segmentation algorithm is developed to satisfy increasing requirement of image segmentation. Fuzzy CMeans is unsupervised method that has been applied for the variety of purposes such as clustering, classification, image segmentation and target recognition. This method can ...

In decision making, crisp ranking is not possible when the entire attribute characteristics and their degree of importance are known precisely. In real world situations decision making takes place in an environment where the goals, the constraints, and the consequences of possible actions are not known precisely. Thus the best condition for classic decision making problem may not be satisfied w...