Analysis and Modelling of Hierarchical Fuzzy Logic Systems

Analysis and Modelling of Hierarchical Fuzzy Logic Systems

Masoud Mohammadian (University of Canberra, Australia)
Copyright: © 2008 |Pages: 10
DOI: 10.4018/jitr.2008100101
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In this article the design and development of a hierarchical fuzzy logic system is investigated. A new method using an evolutionary algorithm for design of hierarchical fuzzy logic system for prediction and modelling of interest rates in Australia is developed. The hierarchical system is developed to model and predict three months (quarterly) interest rate fluctuations. This research study is unique in the way proposed method is applied to design and development of fuzzy logic systems. The new method proposed determines the number of layer for hierarchical fuzzy logic system. The advantages and disadvantages of using fuzzy logic systems for financial modelling is also considered. Conclusions on the accuracy of prediction using hierarchical fuzzy logic systems compared to a back-propagation neural network system and a hierarchical neural network are reported.

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