Fuzzy quantifiers like “few”, “almost”, “about” and many others abound in natural language. They are used by humans for describing uncertain facts, quantitative relations and processes. An adequate contradiction-free computer-operational implementation of these quantifiers would provide a class of powerful yet human-understandable operators both for aggregation and fusion of data but also for s...

This paper addresses the problem of choosing the most appropriate classification from a given set of classifications of a set of patterns. This is a relevant topic on unsupervised systems and clustering analysis because different classifications can in general be obtained from the same data set. The provided methodology is based on five fuzzy criteria which are aggregated using an Ordered Weigh...

This paper presents some preliminary results from a research on spatial multi-criteria evaluation of land suitability for intensification or extensification in irrigated cropland at a catchment scale in Australia. The project was conducted using the fuzzy linguistic ordered weighted averaging (FLOWA) approach which integrates AHP and fuzzy linguistic OWA operators in ArcGIS 9.2 environment. Sev...

In this paper, the texture feature ”coarseness” is modelled by means of a fuzzy partition on the domain of coarseness measures. The number of linguistic labels to be used, and the parameters of the membership functions associated to each fuzzy set are calculated relating representative coarseness measures (our reference set) with the human perception of this texture property. A wide variety of ...

This paper presents a method to construct an interval-valued fuzzy set from a fuzzy set and the representation of the lack of knowledge or ignorance that experts are subject to when they define the membership values of the elements to that fuzzy set. With this construction method, it is proved that membership intervals of equal length to the ignorance associated to the elements are obtained whe...

Ronald R. Yager Machine Intelligence Institute, Iona College New Rochelle, NY 10801 [email protected] (212)249-2047 ABSTRACT Fuzzy sets and other methods have been used to model a softening of constraints in CP problems. Here we suggest an approach to the softening of the CP problem at the meta level, the process used to aggregate the satisfactions to the individual constraints. We suggest the us...

This paper presents a critical analysis of conventional operations on intuitionistic fuzzy values (IFVs), and some limitations of the conventional aggregation operator on IFVs are analyzed in detail. In order to overcome these limitations, according to new operation laws on IFVs based on Achimedean t-norm and t-conorm, we propose a new quasi-intuitionistic fuzzy OWA (QIFOWA) operator. Some corr...

The OWA weighting vector and the fuzzy quantifiers are strictly related. An intuitive way for shaping a monotonic quantifier, is by means of the threshold that makes a separation between the regions of what is satisfactory and what is not. Therefore, the characteristics of a threshold can be directly related to the OWA weighting vector and to its metrics: the attitudinal character and the entro...

This paper presents a fuzzy extension of TOPSIS (technique for order performance by similarity to ideal solution) with a new quantifier guided distance metric and majority opinion aggregator for multi-criteria decision making in a group decision environment. The proposed distance metric is based on OWA aggregators and provides an opportunity to use linguistic quantifiers to have linguistic defi...