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

Masoud Mohammadian; Mark Kingham

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

Masoud Mohammadian, Mark Kingham

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

4 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 language	English
Title of host publication	Advanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings
Publisher	Springer
Pages	147-156
Number of pages	10
ISBN (Print)	3540637974, 9783540637974
Publication status	Published - 1 Jan 1997
Event	10th Australian Joint Conference on Artificial Intelligence, AI 1997 - Perth, Australia Duration: 30 Nov 1997 → 4 Dec 1997

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1342
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th Australian Joint Conference on Artificial Intelligence, AI 1997
Country/Territory	Australia
City	Perth
Period	30/11/97 → 4/12/97

Cite this

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.

Mohammadian, Masoud ; Kingham, Mark. / Hierarchical and feed-forward fuzzy Logic for financial modelling and prediction. Advanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings. Springer, 1997. pp. 147-156 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1342, Springer, pp. 147-156, 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Perth, Australia, 30/11/97.

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

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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AB - 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.

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Mohammadian M, Kingham M. 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. Springer. 1997. p. 147-156. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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

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