Abstract

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

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call