В статье обосновываются преимущества подхода к моделированию процесса трансфера инноваций, построенного на математическом аппарате теории нечетких мер и...

In this paper we present a tool to help reduce the uncertainty presented in the decision-making process associated to the selection and hiring of a professional athlete. A weighted mean hemimetric for fuzzy subsets with trapezoidal fuzzy numbers (TrFN) as their elements, allows to compare...

The aim of this paper is to develop an approach based on fuzzy-sets to handle the uncertainty of nuclear power costs. The underlying aim is to appraise the economic advantages of nuclear power compared with other traditional energy sources, namely coal and natural gas. Having illustrated the...

This book proposes a set of models to describe fuzzy multi-objective decision making (MODM), fuzzy multi-criteria decision making (MCDM), fuzzy group decision making (GDM) and fuzzy multi-objective group decision-making problems, respectively. It also gives a set of related methods (including...

Recently, a Competitive Exception Learning Algorithm (CELA) was introduced [1, 2]. This algorithm establishes an optimal mapping from a (continuous) M-dimensional input sample space to an N-dimensional (continuous) output sample space. CELA is aimed to discover regimes (i.e. local behavior in...

A competitive exception learning algorithm for finding a non-linear mapping is proposed which puts the emphasis on the discovery of the important exceptions rather than the main rules. To do so,we first cluster the output space using a competitive fuzzy clustering algorithm and derive a fuzzy...

Using the statistical technique of fuzzy clustering, regimes of inflation and unemployment are explored for the United States, the United Kingdom and Germany between 1871 and 2009. We identify for each country three distinct regimes in inflation/unemployment space. There is considerable...