This article addresses the fuzziness in regression models. The goal is to present a test procedure to explicitly examine whether an independent variable has a clear functional relationship with the dependent variable in a specific regression model, or whether their relationship is fuzzy. To this end, we interpret the spread of the regression coefficients as a statistic measuring the fuzziness o...

In applications there occur different forms of uncertainty. The twomost important types are randomness (stochastic variability) and imprecision(fuzziness). In modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. However, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.Since many years t...

Recent progress in supervised image classification research, has demonstrated the potential usefulness of incorporating fuzziness in the training, allocation and testing stages of several classification techniques. In this paper a multiresolution neural network approach to supervised classification is presented, exploiting the inherent fuzziness of such techniques in order to perform classifica...

This paper describes a generic strategy for “intelligently” querying hierarchical semantic networks whose objects are characterized by fuzzy attributes. The strategy is self-adaptable in the sense that the network will keep structuring itself (as long as the user queries the system) by adding more and more detail to an underlying semi-lattice built on top of a (fuzzy) object comparison partial ...

The main aim of the investigation of hedge algebras is to discover an algebraic structure in the category of universal algebras of terms-domains of linguistic variables or to establish an algebraic approach to the semantic structure of terms-domains. The meaning of linguistic terms in general is vague, however vagueness is a concept which is difficult to be defined formally and reasonably. Moti...

In this paper, the Fuzzy Vector Median is proposed, defined as an extension of Vector Median. It is based on a novel distance definition of multidimensional fuzzy numbers (fuzzy vectors), which satisfy the property of angle decomposition. The proposed distance of two fuzzy vectors depends on the classical distance of the fuzzy set centers and on the fuzziness that every fuzzy set holds. As a re...

The theory of fuzzy sets with reference to subnormality needs to be properly explained. We shall in this article put forward the actual mathematical explanation of subnormal partial presence of an element in a set, better known as subnormal fuzziness. We shall first show that every law of subnormal fuzziness can be expressed in terms of two Lebesgue-Stieltjes measures. Thereafter we would defin...

Abstract — This paper considers a linear programming problem with ellipsoidal distributions including fuzziness. Since this problem is not well-defined due to randomness and fuzziness, it is hard to solve it directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed model is transformed into the deterministic equivalent problems. Furthermore, since i...

A problem which must be dealt with by any reasonably general computer simulation of the cognitive processes underlying natural language dialogue behaviour is the inherent fuzziness of natural language and human thought. Artificial Intelligence (AI) research has to date achieved nothing approaching a general formal treatment covering all aspects of fuzziness. Surveys of AI approaches to the prob...

In this paper we present some preliminary ideas about how to formally relate various uncertainty representations together in a taxonomic structure, capturing both syntactic and semantic generalization. Fuzziness and nonspeciicity are presumed as primitive concepts of uncertainty, and transitive and intransitive methods operating with nonspeciicity and fuzziness are introduced to generate a base...