Model Optimisation for Complex Systems using Fuzzy Networks Theory

نویسندگان

  • NEDYALKO PETROV
  • ALEXANDER GEGOV
چکیده

This paper presents an application of the novel theory of fuzzy networks for optimising models of systems characterised by uncertainty, non-linearity, modular structure and interactions. The application of the theory is demonstrated for retail price models in the context of converting a multiple rule base fuzzy system (MRBFS) into an equivalent single rule base fuzzy system (SRBFS) by linguistic composition of the individual rule bases. During the conversion process, the transparency of the MRBFS is fully preserved while its accuracy is improved to a level comparable with the accuracy of the SRBFS. This improvement is achieved by increasing the number of linguistic terms for the intermediate variable connecting the individual rule bases. Key-Words: Complex systems, fuzzy systems, fuzzy networks, rule bases, rule based systems, composition models, retail pricing, multiple rule base fuzzy systems, single rule base systems.

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تاریخ انتشار 2009