A Genetic Type-2 fuzzy logic based system for financial applications modelling and prediction
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- @InProceedings{Bernardo:2013:ieeeFUZZ,
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author = "Dario Bernardo and Hani Hagras and Edward Tsang",
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title = "A Genetic Type-2 fuzzy logic based system for
financial applications modelling and prediction",
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booktitle = "IEEE International Conference on Fuzzy Systems (FUZZ
2013)",
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year = "2013",
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month = jul,
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keywords = "genetic algorithms, genetic programming, type-2 fuzzy
logic",
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DOI = "doi:10.1109/FUZZ-IEEE.2013.6622310",
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ISSN = "1098-7584",
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abstract = "Following the global economic crisis, many financial
organisations around the World are seeking efficient
frameworks for predicting and assessing financial
risks. However, in the current economic situation,
transparency became an important factor where there is
a need to fully understand and analyse a given
financial model. In this paper, we will present a
Genetic Type-2 Fuzzy Logic System (FLS) for the
modelling and prediction of financial applications. The
proposed system is capable of generating summarised
optimised type-2 FLSs based financial models which are
easy to read and analyse by the lay user. The system is
able to use the summarised model for prediction within
financial applications. We have performed several
evaluations in two distinctive financial domains one
for the prediction of good/bad customers in a credit
card approval application and the other domain was in
the prediction of arbitrage opportunities in the stock
markets. The proposed Genetic type-2 FLS has
outperformed white box financial models like the
Evolving Decision Rule (EDR) procedure (which is based
on Genetic Programming (GP) and decision trees) and
gave a comparable performance to black box models like
neural networks while the proposed system provided a
white box model which is easy to understand and analyse
by the lay user.",
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notes = "Also known as \cite{6622310}",
- }
Genetic Programming entries for
Dario Bernardo
Hani Hagras
Edward P K Tsang
Citations