A MEP and IP Based Flexible Neural Tree Model for Exchange Rate Forecasting

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@InProceedings{Jia:2008:ICNC,

• author = "Guangfeng Jia and Yuehui Chen and Qiang Wu",
• title = "A MEP and IP Based Flexible Neural Tree Model for Exchange Rate Forecasting",
• booktitle = "Fourth International Conference on Natural Computation, ICNC '08",
• year = "2008",
• month = oct,
• volume = "5",
• pages = "299--303",
• 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)",
• DOI = "doi:10.1109/ICNC.2008.669",
• 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.",
• notes = "Also known as \cite{4667445}",

}

Genetic Programming entries for Guangfeng Jia Yuehui Chen Qiang Wu

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