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An RVML extension for modeling fuzzy rule bases

Авторы: Dorodnykh N.O., Yurin A.Y.

Журнал: CEUR Workshop Proceedings: 1st International Workshop on Advanced Information and Computation Technologies and Systems (AICTS 2020, Irkutsk, 7-11 December 2020)

Том: 2858


Год: 2021

Отчётный год: 2021


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Аннотация: 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.

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