A MEP and IP Based Flexible Neural Tree Model for Exchange Rate Forecasting
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- @InProceedings{Jia:2008:ICNC,
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author = "Guangfeng Jia and Yuehui Chen and Qiang Wu",
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title = "A MEP and IP Based Flexible Neural Tree Model for
Exchange Rate Forecasting",
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booktitle = "Fourth International Conference on Natural
Computation, ICNC '08",
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year = "2008",
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month = oct,
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volume = "5",
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pages = "299--303",
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keywords = "genetic algorithms, genetic programming, MEP,
financial problem, flexible neural tree model, foreign
exchange rate forecasting, immune programming, multi
expression programming, exchange rates, financial
management, neural nets, trees (mathematics)",
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DOI = "doi:10.1109/ICNC.2008.669",
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abstract = "Forecasting exchange rate is an important financial
problem that is received much more attentions because
of its difficulty and practical applications. The
problem of prediction of foreign exchange rates by
using multi expression programming and immune
programming based flexible neural tree (MEPIP-FNT) is
presented in this paper. This work is an extension of
our previously traditional FNT model which can optimize
the architectures and the weights of flexible neuron
model respectively. The novel MEPIPFNT model with the
underlying immune theories is capable of evolving the
architectures and the weights simultaneously. To
demonstrate the efficiency of the model, we conduct
three different datasets in our forecasting performance
analysis.",
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notes = "Also known as \cite{4667445}",
- }
Genetic Programming entries for
Guangfeng Jia
Yuehui Chen
Qiang Wu
Citations