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Innovative Design of Adaptive Hierarchical Fuzzy Logic Systems
Author(s) -
Masoud Mohammadian
Publication year - 2005
Publication title -
international conference on computational intelligence for modelling, control and automation and international conference on intelligent agents, web technologies and internet commerce (cimca-iawtic'06)
Language(s) - English
DOI - 10.1109/cimca.2005.13
In this paper the supervised and unsupervised fuzzy concept learning using evolutionary algorithms is considered. The paper explores the design and development of hierarchical fuzzy logic systems using an evolutionary algorithm. The development of hierarchical fuzzy logic systems is considered by a new method which determines the number of layers in the hierarchical fuzzy logic system. 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. Finally evolutionary algorithm is then used to design a fuzzy logic system from a set of data in an unsupervised learning manner. Specifically it's application to urban traffic control is considered

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