Affiliations: [a]
University of Portsmouth, School of Computing, Buckingham Building, Portsmouth, UK
| [b]
University of Portsmouth, School of Engineering, Angleasea Building, Portsmouth, UK
| [c]
Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria
Correspondence:
[*]
Corresponding author. Alexander Gegov, University of Ports-mouth, School of Computing, Buckingham Building, Portsmouth PO1 3HE, UK. Tel.: +44 (0)23 9284 6381; +44 (0)23 9284 6364; E-mail: [email protected].
Abstract: This paper proposes a novel approach for modelling complex interconnected systems by means of Mamdani fuzzy networks with feedforward rule bases. The nodes in these networks are rule bases connected in a feedforward manner whereby outputs from some rule bases are fed as inputs to subsequent rule bases. The approach allows any fuzzy network of this type to be presented as an equivalent Mamdani 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 horizontal levels and vertical layers. The proposed approach facilitates the understanding of complex interconnected systems by improving the transparency of their models.
Keywords: Fuzzy modelling, decision support systems, finance, linguistic modelling, feedforward connections, complex systems
