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A Transformation-Based Approach for Fuzzy Knowledge Bases Engineering

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Part of the Studies in Systems, Decision and Control book series (SSDC,volume 337)

Abstract

Fuzzy knowledge base engineering remains an important area of scientific research. The efficiency of this process can be improved due to the automated analysis of existing domain models in the form of conceptual diagrams of different types. In this paper we propose an approach for generating knowledge bases by transforming conceptual models with fuzzy factors. Resulted knowledge bases contain fuzzy rules. The proposed approach includes: a method for the automated analysis and transformation of conceptual models serialized in the XML-like formats; an extended domain-specific declarative language for describing transformation models, namely Transformation Model Representation Language (TMRL); a software module for Knowledge Base Development System (KBDS) that implements the proposed method. Our approach was used for prototyping a knowledge base for predicting degradation processes of technical systems in the petrochemical industry, in this case we developed the software module for transformation of Ishikawa diagrams that account fuzzy and uncertainty factors.

Keywords

  • Model-driven engineering
  • Model transformation
  • Metamodel
  • Code generation
  • Fuzzy conceptual model
  • Fuzzy knowledge base
  • Fuzzy rules
  • TMRL
  • Ishikawa diagrams

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Correspondence to Aleksandr Yurin .

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Dorodnykh, N., Nikolaychuk, O., Yurin, A. (2021). A Transformation-Based Approach for Fuzzy Knowledge Bases Engineering. In: , et al. Recent Research in Control Engineering and Decision Making. ICIT 2020. Studies in Systems, Decision and Control, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-65283-8_7

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