Vassia Atanassova

InterCriteria Decision Making Approach to EU Member States Competitiveness Analysis: Temporal and Threshold Analysis

In this paper, we present some interesting findings from the application of our recently developed InterCriteria Decision Making (ICDM) approach to data extracted from the World Economic Forum’s Global Competitiveness Reports for the years 2008–2009 to 2013–2014 for the current 28 Member States of the European Union. The developed approach which employs the apparatuses of index matrices and intuitionistic fuzzy sets is designed to produce from an existing index matrix with multiobject multicriteria evaluations a new index matrix that contains intuitionistic fuzzy pairs with the correlations revealed to exist in between the set of evaluation criteria, which are not obligatory there ‘by design’ of the WEF’s methodology but exist due to the integral, organic nature of economic data. Here, we analyse the data from the six-year period within a reasonably chosen intervals for the thresholds of the intuitionistic fuzzy functions of membership and non-membership, and make a series of observations about the current trends in the factors of competitiveness of the European Union. The whole research and the conclusions derived are in line with WEF’s address to state policy makers to identify and strengthen the transformative forces that will drive future economic growth.

InterCriteria Decision Making Approach to EU Member States Competitiveness Analysis: Trend Analysis

In this paper, we continue our investigations of the newly developed InterCriteria Decision Making (ICDM) approach with considerations about the more appropriate choice of the employed intuitionistic fuzzy threshold values. In theoretical aspect, our aim is to identify the relations between the thresholds of inclusion of new elements to the set of strictly correlating criteria and the numbers of correlating pairs of criteria thus formed. We illustrate the findings with data extracted from the World Economic Forum’s Global Competitiveness Reports for the years 2008–2009 to 2013–2014 for the current 28 Member States of the European Union. The study of the findings from the considered six-year period involves trend analysis and computation of two approximating functions: a linear function and a polynomial function of 6th order. The per-year trend analysis of each of the 12 criteria, called ‘pillars of competitiveness’ in the WEF’s GCR methodology, gives an opportunity to prognosticate their values for the forthcoming year 2014–2015.

Investigation of relationships between bulk properties and fraction properties of crude oils by application of the intercriteria analysis

ABSTRACT Data from assays of 244 crude oils (condensates, extra light, light, intermediate, and heavy crudes) were processed by the InterCriteria Analysis with the aim to investigate the relationships between bulk properties and fraction properties of the crude oils and the degree of similarity between them. It was found that except the crude bulk properties sulfur, Conradson carbon, and metals content all other studied crude bulk properties exhibited lack of statistically meaningful relations or presence of weak statistically meaningful relations with the crude fraction properties. The use of the InterCriteria Analysis showed that crudes with very similar properties could be identified when a large crude database is available. In this way based on a previous experience in oil refining a selection of potentially beneficial new crudes for processing in a refinery could be made.

Intercriteria analysis of calorimetric data of blood serum proteome

BACKGROUND Biological microcalorimetry has entered into a phase where its potential for disease diagnostics is readily recognized. A wide variety of oncological and immunological disorders have been characterized by differential scanning calorimetry (DSC) and characteristic thermodynamic profiles were reported. Now the challenge before DSC is not the experimental data collection but the development of analysis protocols for reliable data stratification/classification and discrimination of disease specific features (calorimetric markers). METHODS In this work we apply InterCriteria Analysis (ICA) approach combined with Pearsons and Spearmans correlation analysis to a large dataset of calorimetric and biochemical parameters derived for the serum proteome of patients diagnosed with multiple myeloma (MM). RESULTS We have identified intercriteria dependences that are general for the various types of MM and thus can be regarded as a characteristic of this largely heterogeneous disease: strong contribution of the monoclonal (M) protein concentration to the excess heat capacity of the immunoglobulins-assigned thermal transition; shift of the albumin assigned calorimetric transition to allocation where it overlaps with the globulins assigned transition and strong shift of the globulins assigned transition temperature attributable to M proteins conformational changes. CONCLUSIONS Our data justify the applicability of ICA for deciphering of the complex thermodynamic behavior of the MM blood serum proteome. GENERAL SIGNIFICANCE The applied approach is suitable for more general application in the analysis of biocalorimetric data since it can help identify the biological relevance of the distinguished thermodynamic features observed for variety of diseases.

Intercriteria analysis over normalized data

The possibility to apply the intercriteria analysis over normalized data is discussed. An example, related to evaluation of crude oil data, is given.

Generalized net model of Cuckoo search algorithm

In this paper the apparatus of generalized nets is applied to describe the Cuckoo search (CS). The CS is a metaheuristic population-based algorithm inspired by the brood parasitism of some cuckoo species laying their eggs in the nests of other bird species. In addition, CS is enhanced by the so-called Lévy flights rather than by simple isotropic random walks. Preliminary studies show that CS is very promising and could outperform existing algorithms such as Particle Swarm Optimization, Genetic Algorithms, and other algorithms. The proposed herewith model provides the opportunity to describe the logic of CS in the terms of the mathematical modeling paradigm of generalized nets.

Intuitionistic fuzzy statistical tools for filters in image processing

Theoretical aspects like sample mean, median, and mode of intuitionistic fuzzy (IF) data are defined. These concepts are very much useful in obtaining IF filters in image processing.

Intercriteria Analysis over Intuitionistic Fuzzy Data

The possibility for application of Intercriteria Analysis over intuitionistic fuzzy data is discussed. An example in the area of mathematical logic is given as an illustration of the application of the Intercriteria Analysis.

Traversing and Ranking of Elements of an Intuitionistic Fuzzy Set in the Intuitionistic Fuzzy Interpretation Triangle

In this leg of research, we explore the question of traversing and ranking elements of an intuitionistic fuzzy set in the intuitionistic fuzzy interpretation triangle. This is necessary in the light of the new developments of the InterCriteria Analysis (ICA), a decision support approach based on intuitionistic fuzzy sets and index matrices. In the ICA, from the data about the evaluations or measurements of a set of objects against a set of criteria, we perform pairwise comparisons of any two objects against each pair of criteria, and perform computations that yield in result intuitionistic fuzzy pairs of numbers in the [0; 1]-interval that give the levels of correlation between any two of the evaluation criteria. In previous works, the correlations between the criteria (hence the term ‘intercriteria’) were analysed separately, by first setting priority on either the membership, or the non-membership component, and plotting them linearly; while currently the efforts are oriented to handling both IF components simultaneously by plotting them in the plane of the intuitionistic fuzzy interpretation triangle.

New Modified Level Operator N γ Over Intuitionistic Fuzzy Sets

The present paper takes the idea of the level operator N α,β and proposes a modification called N γ . The aim of the original level operator is to generate a subset of an intuitionistic fuzzy set A, called (α, β)-set, whose degrees of membership are above a given level (threshold) α and degrees of non-membership are below a given level β, where both α, β are fixed numbers in the [0, 1] interval and α + β ≤ 1. In the modification proposed here, we introduce the operator N γ that also generates a subset of an intuitionistic fuzzy set A, where the elements of the subset are those elements of A, for which the ratio of their degrees of membership to their degrees of non-membership, respectively, is greater or equal to a given number γ > 0.