AINov 10, 2022
Fuzziness, Indeterminacy and Soft Sets: Frontiers and PerspectivesMichael Gr. Voskoglou
The present paper comes across the main steps that laid from Zadeh's fuzziness ana Atanassov's intuitionistic fuzzy sets to Smarandache's indeterminacy and to Molodstov's soft sets. Two hybrid methods for assessment and decision making respectively under fuzzy conditions are also presented through suitable examples that use soft sets and real intervals as tools. The decision making method improves an earlier method of Maji et al. Further, it is described how the concept of topological space, the most general category of mathematical spaces, can be extended to fuzzy structures and how to generalize the fundamental mathematical concepts of limit, continuity compactness and Hausdorff space within such kind of structures. In particular, fuzzy and soft topological spaces are defined and examples are given to illustrate these generalizations.
AIMay 16, 2023
An Application of Neutrosophic Sets to Decision MakingMichael Gr. Voskoglou
Maji et al. introduced in 2002 a method of parametric decision making using soft sets as tools and representing their tabular form as a binary matrix. In cases, however, where some or all of the parameters used for the characterization of the elements of the universal set are of fuzzy texture, their method does not give always the best decision making solution. In order to tackle this problem, we modified in earlier works the method of Maji et al. by replacing the binary elements in the tabular form of the corresponding soft set either by grey numbers or by triangular fuzzy numbers. In this work, in order to tackle more efficiently cases in which the decision maker has doubts about the correctness of the fuzzy/qualitative characterizations assigned to some or all of the elements of the universal set, we replace the binary elements of the tabular form by neutrosophic triplets. Our new, neutrosophic decision making method is illustrated by an application concerning the choice of a new player by a soccer club.
AIApr 2, 2018
Application of Grey Numbers to Assessment ProcessesMichael Gr. Voskoglou, Yiannis Theodorou
The theory of grey systems plays an important role in science,engineering and in the everyday life in general for handling approximate data. In the present paper grey numbers are used as a tool for assessing with linguistic expressions the mean performance of a group of objects participating in a certain activity. Two applications to student and football player assessment are also presented illustrating our results.
AIApr 2, 2018
A Study of Student Learning Skills Using Fuzzy Relation EquationsMichael Gr. Voskoglou
Fuzzy relation equations (FRE)are associated with the composition of binary fuzzy relations. In the present work FRE are used as a tool for studying the process of learning a new subject matter by a student class. A classroom application and other csuitable examples connected to the student learning of the derivative are also presented illustrating our results and useful conclusions are obtained.
AINov 30, 2016
Comparison of the COG Defuzzification Technique and Its Variations to the GPA IndexMichael Gr. Voskoglou
The Center of Gravity (COG) method is one of the most popular defuzzification techniques of fuzzy mathematics. In earlier works the COG technique was properly adapted to be used as an assessment model (RFAM)and several variations of it (GRFAM, TFAM and TpFAM)were also constructed for the same purpose. In this paper the outcomes of all these models are compared to the corresponding outcomes of a traditional assessment method of the bi-valued logic, the Grade Point Average (GPA) Index. Examples are also presented illustrating our results.
AIJan 8, 2016
An Application of the Generalized Rectangular Fuzzy Model to Critical Thinking AssessmentIgor Ya. Subbotin, Michael Gr. Voskoglou
The authors apply the Generalized Rectangular Model to assessing critical thinking skills and its relations with their language competency.
AIMay 29, 2014
Analogy-Based and Case-Based Reasoning: Two sides of the same coinMichael Gr. Voskoglou, Abdel-Badeeh M. Salem
Analogy-Based (or Analogical) and Case-Based Reasoning (ABR and CBR) are two similar problem solving processes based on the adaptation of the solution of past problems for use with a new analogous problem. In this paper we review these two processes and we give some real world examples with emphasis to the field of Medicine, where one can find some of the most common and useful CBR applications. We also underline the differences between CBR and the classical rule-induction algorithms, we discuss the criticism for CBR methods and we focus on the future trends of research in the area of CBR.
AIApr 29, 2014
Assessing the players'performance in the game of bridge: A fuzzy logic approachMichael Gr. Voskoglou
Contract bridge occupies nowadays a position of great prestige being, together with chess, the only mind games officially recognized by the International Olympic Committee. In the present paper an innovative method for assessing the total performance of bridge- players' belonging to groups of special interest(e.g. different bridge clubs during a tournament, men and women, new and old players, etc) is introduced, which is based on principles of fuzzy logic. For this, the cohorts under assessment are represented as fuzzy subsets of a set of linguistic labels characterizing their performance and the centroid defuzzification method is used to convert the fuzzy data collected from the game to a crisp number. This new method of assessment could be used informally as a complement of the official bridge-scoring methods for statistical and other obvious reasons. Two real applications related to simultaneous tournaments with pre-dealt boards, organized by the Hellenic Bridge Federation, are also presented, illustrating the importance of our results in practice.
AIJan 4, 2014
A stochastic model for Case-Based ReasoningMichael Gr. Voskoglou
Case-Bsed Reasoning (CBR) is a recent theory for problem-solving and learning in computers and people.Broadly construed it is the process of solving new problems based on the solution of similar past problems. In the present paper we introduce an absorbing Markov chain on the main steps of the CBR process.In this way we succeed in obtaining the probabilities for the above process to be in a certain step at a certain phase of the solution of the corresponding problem, and a measure for the efficiency of a CBR system. Examples are given to illustrate our results.
AINov 21, 2013
Dealing with the Fuzziness of Human ReasoningMichael Gr. Voskoglou, Igor Ya. Subbotin
Reasoning, the most important human brain operation, is charactrized by a degree fuzziness. In the present paper we construct a fuzzy model for the reasoning process giving through the calculation of the possibilities of all possible individuals' profiles a quantitative/qualitative view of their behaviour during the above process and we use the centroid defuzzification technique for measuring the reasoning skills. We also present a number of classroom experiments illustrating our results in practice.
AIApr 28, 2012
A Fuzzy Model for Analogical Problem SolvingMichael Gr. Voskoglou
In this paper we develop a fuzzy model for the description of the process of Analogical Reasoning by representing its main steps as fuzzy subsets of a set of linguistic labels characterizing the individuals' performance in each step and we use the Shannon- Wiener diversity index as a measure of the individuals' abilities in analogical problem solving. This model is compared with a stochastic model presented in author's earlier papers by introducing a finite Markov chain on the steps of the process of Analogical Reasoning. A classroom experiment is also presented to illustrate the use of our results in practice.
AIApr 10, 2012
Applications of fuzzy logic to Case-Based ReasoningIgor Ya. Subbotin, Michael Gr. Voskoglou
The article discusses some applications of fuzzy logic ideas to formalizing of the Case-Based Reasoning (CBR) process and to measuring the effectiveness of CBR systems