Building Decision Support Systems based on Fuzzy Data

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DOI: https://doi.org/10.20998/2522-9052.2020.4.07
Keywords:
decision making support systems, fuzzy logic, fuzzy decision trees

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Vitaly Levashenko
University of Žilina, Žilina
https://orcid.org/0000-0003-1932-3603
Oleksii Liashenko
Kharkiv National University of Radio Electronics, Kharkiv
https://orcid.org/0000-0002-0146-3934
Heorhii Kuchuk
National Technical University "Kharkiv Polytechnic Institute", Kharkiv
https://orcid.org/0000-0002-2862-438X

Abstract

The implementation of tools for assessing decisions making is an urgent and demanded task at the current stage of information technology development. Decision-making support systems (DMSS) are perspective tools for it. The paper proposes a mathematical tool for construction a DMSS. DMSS construction involves the analysis of the available observation or measurement results and the development of a strategy for checking the initial parameters in the form of a fuzzy decision tree or production rules. The proposed tool is based on cumulative information estimates (information and entropy) for fuzzy data sets. The use of fuzzy data is a most fully consistent with human nature. It can be explained, that in practice people often use subjective sensations and a priori knowledge than precise probabilistic criteria. Therefore, using fuzzy logic and considering the degree of possibility as a fuzzy measure, experts are able to describe real data with sufficient accuracy. The relationship of the proposed total information estimates is investigated in the paper. The paper provides examples which demonstrating the practical application of the proposed mathematical tool. The authors plan to present the results of experimental investigations of the proposed approach and its comparison with other known methods and algorithms in a next work. These results will be obtained on a wide range of formalized data stored in the well-known UCI Machine Learning Repository. As compared methods and algorithms, we are going to choose algorithms for constructing fuzzy decision trees based on Luca de Termini entropy, Naive-Bayesian classification, algorithms for decision trees induction - C4.5, CART and the method of nearest neighbours.

Article Details

How to Cite
Levashenko, V., Liashenko, O., & Kuchuk, H. (2020). Building Decision Support Systems based on Fuzzy Data. Advanced Information Systems, 4(4), 48–56. https://doi.org/10.20998/2522-9052.2020.4.07
Issue
Vol. 4 No. 4 (2020): Advanced Information Systems
Section
Methods of information systems synthesis
Author Biographies

Vitaly Levashenko, University of Žilina, Žilina

Professor, Head of the Department of Informatics, Faculty of Management Science and Informatics

Oleksii Liashenko, Kharkiv National University of Radio Electronics, Kharkiv

Candidate of Technical Sciences, Associate Professor, Dean of Faculty of Computer Engineering and Control

Heorhii Kuchuk, National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Doctor of Technical Sciences, Professor, Professor of Computer Science and Programming Department

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