Open AccessAn RVML extension for modeling fuzzy rule bases
Author(s) -
Nikita O. Dorodnykh,
Aleksandr Yu. Yurin
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.47350/aicts.2020.04
Subject(s) - computer science , extension (predicate logic) , programming language , notation , fuzzy logic , fuzzy rule , artificial intelligence , knowledge base , generative grammar , software engineering , fuzzy set , mathematics , arithmetic
Rules are still the most widespread way to represent expert knowledge despite the popularity of semantic technologies. The effective use of rules in decision-making in the case of inaccurate or uncertain information requires the development of specialized means and software for visual and generative programming. This paper considers an extension of the Rule Visual Modeling Language called FuzzyRVML designed for modeling fuzzy rule bases. FuzzyRVML supports a fuzzy datatype, concepts of a linguistic variable, terms, and certainty factors. The descriptions of FuzzyRVML basic elements, main constructions, and an illustrative example containing FuzzyCLIPS source code generation are presented. The evaluation and implementation of this notation are made based on the Personal Knowledge Base Designer software.