Designing Layers in Hierarchical Fuzzy Logic Systems Using Genetic Algorithms

Designing Layers in Hierarchical Fuzzy Logic Systems Using Genetic Algorithms

Masoud Mohammadian (University of Canberra, Australia) and Russel Stonier (Central Queensland University, Australia)
DOI: 10.4018/978-1-59904-249-7.ch005
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Abstract

In this paper the design and development of hierarchical fuzzy logic systems is investigated using genetic algorithms. This research study is unique in the way the proposed method is applied to the design and development of hierarchical fuzzy logic systems. The new method proposed determines the number of layers in the hierarchical fuzzy logic system. The proposed method is then applied to financial modelling and prediction. A hierarchical fuzzy logic system is developed to predict quarterly interest rates in Australia. The advantages and disadvantages of using hierarchical fuzzy logic systems for financial modelling is also considered. Good prediction of quarterly interest rate in Australia is obtained using the above method. The number of fuzzy rules used is reduced dramatically and prediction of interest rate is improved.

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