4.7 Article

Intuitionistic fuzzy logics as tools for evaluation of Data Mining processes

Journal

KNOWLEDGE-BASED SYSTEMS
Volume 80, Issue -, Pages 122-130

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2015.01.015

Keywords

Artificial intelligence; Data Mining; Intuitionistic fuzzy estimation; Intuitionistic fuzzy logics; Intuitionistic fuzzy set

Funding

  1. Editors of Journal Knowledge-Based Systems
  2. Bulgarian National Science Fund [DFNI-I-02/5]

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The Intuitionistic Fuzzy Sets (IFSs), proposed in 1983, are extensions of fuzzy sets. Some years after their introduction, sequentially, intuitionistic fuzzy propositional logic, intuitionistic fuzzy predicate logic, intuitionistic fuzzy modal logic and intuitionistic fuzzy temporal logic have been introduced, presented here shortly. During the last 25 years, different intuitionistic fuzzy tools have been used for evaluation of objects from the area of the Artificial Intelligence, as expert systems (having, e.g. facts and rules, with intuitionistic fuzzy degrees of validity and non-validity), decision making processes (having, e.g. intuitionistic fuzzy estimations of the criteria), neural networks, pattern recognitions, metaheuristic algorithms, etc. Short review of these legs of research is offered, with some concrete ideas of possible new directions of study. On this basis, a non-formal discussion is raised on the benefits of applying various elements of intuitionistic fuzzy logics as tools for evaluation of Data Mining processes. (C) 2015 Elsevier B.V. All rights reserved.

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