Designing Customized Hierarchical Fuzzy Logic Systems for Modelling and Prediction

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    Abstract

    In this paper the design and development of a hierarchical fuzzy logic Systems are investigated. A new method using genetic algorithms for design of hierarchical fuzzy logic systems are proposed. This research study is unique in the way proposed method is applied to design and development of hierarchical fuzzy logic systems. 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 new method proposed
    determines the number of layer in a hierarchical fuzzy logic system. 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 rule used are reduced dramatically and prediction of interest rate is improved.
    Original languageEnglish
    Title of host publicationICONIP'02-SEAL'02-FSKD'02
    EditorsLipo Wang, Jagath C. Rajapakse, Kunihiko Fukushima
    Place of PublicationSingapore
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1-5
    Number of pages5
    ISBN (Print)9810475241
    Publication statusPublished - 2002
    Event4th Asia-Pacific Conference on Simulated Evolution and Learning - , Singapore
    Duration: 18 Nov 200222 Nov 2002

    Conference

    Conference4th Asia-Pacific Conference on Simulated Evolution and Learning
    CountrySingapore
    Period18/11/0222/11/02

      Fingerprint

    Cite this

    Mohammadian, M. (2002). Designing Customized Hierarchical Fuzzy Logic Systems for Modelling and Prediction. In L. Wang, J. C. Rajapakse, & K. Fukushima (Eds.), ICONIP'02-SEAL'02-FSKD'02 (pp. 1-5). Singapore: IEEE, Institute of Electrical and Electronics Engineers.