Affiliations: [a] School of Computing Buckingham Building, University of Portsmouth, Portsmouth PO1 3HE, UK | [b] School of Engineering Anglesea Building, University of Portsmouth, Portsmouth PO1 3DJ, UK | [c] Institute of Information and Communication Technologies Block 2, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Correspondence:
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Corresponding author: Alexander Gegov, School of Computing Buckingham Building, University of Portsmouth, Portsmouth PO1 3HE, UK. E-mail:alexander.gegov@port.ac.uk
Abstract: This paper proposes a novel approach for modelling
complex interconnected systems by means of fuzzy networks. The nodes in
these networks are interconnected rule bases whereby outputs from some rule
bases are fed as inputs to other 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 and basic operations in such networks.
These models and operations are used for defining several node
identification cases in fuzzy networks. In this case, the unknown nodes are
derived by solving Boolean matrix equations in a way that guarantees a
pre-specified overall performance of the network. The main advantage of the
proposed approach over other approaches is that it has better transparency
and facilitates not only the analysis but also the design of complex
interconnected systems.
Keywords: Fuzzy modelling, linguistic modelling, fuzzy networks, network connections, node identification, complex systems
