Hierarchical and feed-forward fuzzy Logic for financial modelling and prediction

Masoud Mohammadian, Mark Kingham

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

3 Citations (Scopus)

Abstract

In this paper, the development of a Hierarchical and Feed-Forward intelligent Fuzzy Logic system using Genetic Algorithms for prediction and modelling of fluctuations in interest rates in Australia is discussed. The system developed is used to predict quarterly and half yearly interest rates using fuzzy logic. The fuzzy rules for fuzzy logic predictor are unknown. A knowledge base must be created from the available data. In the paper Genetic Algorithm is proposed as a method for learning the fuzzy rules of the fuzzy logic predictor. A Hierarchical and Feed-Forward Fuzzy Logic system consisting of five fuzzy knowledge bases is developed to solve the prediction problem.

Original languageEnglish
Title of host publicationAdvanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings
PublisherSpringer-Verlag London Ltd.
Pages147-156
Number of pages10
ISBN (Print)3540637974, 9783540637974
Publication statusPublished - 1 Jan 1997
Event10th Australian Joint Conference on Artificial Intelligence, AI 1997 - Perth, Australia
Duration: 30 Nov 19974 Dec 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1342
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Australian Joint Conference on Artificial Intelligence, AI 1997
CountryAustralia
CityPerth
Period30/11/974/12/97

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    Mohammadian, M., & Kingham, M. (1997). Hierarchical and feed-forward fuzzy Logic for financial modelling and prediction. In Advanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings (pp. 147-156). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1342). Springer-Verlag London Ltd..