A random variable is a whose components are values. To characterise variable, the arithmetic mean widely used as an estimate of location parameter, and variation scale parameter. The disadvantage that it sensitive to extreme values, outliers in data. Due that, variables, robust estimates parameters used: median absolute deviation from median. In real situations, cannot always be estimated deter...

In the last years, the Authors have proposed the use of the Random-Fuzzy Variables (RFVs) to represent measurements results. An RFV is an extension of a fuzzy variable, which is the natural variable in the mathematical possibility theory (in the same way the random variable is the natural variable in the probability theory). The aim of this presentation is to show, through a remotely controlled...

The real life problems deal with imperfectly specified knowledge and some degree of imprecision, uncertainty or inconsistency is embedded in the problem specification. The well-founded theory of fuzzy sets is a special way to model the uncertainty. The rules in a fuzzy model contain a set of propositions, each of which restricts a fuzzy variable to a single fuzzy value by means of the predicate...

The Fuzzy Adaptive Resonance Theory (Fuzzy ART) is an unsupervised neural network and allows both binary and continuous input patterns. In this study, we propose a Fuzzy ART Combining Overlapped Categories Using Variable Vigilance Parameters. The vigilance parameters of the proposed method are arranged for every category, and they are varied according to the size of respective categories with l...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

The problem of sparse fuzzy rule bases is introduced. Because of the high computational complexity of the original compositional rule of inference (CRI) method, it is strongly suggested that the number of rules in a final fuzzy knowledge base is drastically reduced. Various methods of analogical reasoning available in the literature are reviewed. The mapping style interpretation of fuzzy rules ...

The concept of fuzzy random variable has been shown to be as a valuable model for handling fuzzy data in statistical problems. The theory of fuzzy-valued random elements provides a suitable formalization for the management of fuzzy data in the probabilistic setting. A concise overview of fuzzy random variables, focussed on the crucial aspects for data analysis, is presented. © 2006 Elsevier B.V...