Fuzzy networks with feedback rule bases for complex systems modelling

Alexander Gegov, Farzad Arabikhan, David Sanders, Boriana Vatchova, Tanya Vasileva

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Abstract

This paper proposes a novel approach for modelling complex interconnected systems by means of fuzzy networks with feedback rule bases. The nodes in these networks are rule bases connected in a feedback manner whereby outputs from some rule bases are fed as inputs to the same or preceding rule bases. The approach allows any fuzzy network of this type to be presented as an equivalent fuzzy system by linguistic composition of its nodes. The composition process makes use of formal models for fuzzy networks, basic operations in such networks, their properties and advanced operations. These models, operations and properties are used for defining several types of networks with single or multiple local and global feedback. The proposed approach facilitates the understanding of complex interconnected systems by improving the transparency of their models.
Original languageEnglish
Pages (from-to)211-225
Number of pages15
JournalInternational Journal of Knowledge-Based and Intelligent Engineering Systems
Volume21
Issue number4
DOIs
Publication statusPublished - 31 Oct 2017

Keywords

  • fuzzy modelling
  • decision support systems
  • financial modelling
  • linguistic modelling
  • feedback connections
  • complex systems

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