Forecasting Euro - United States Dollar Exchange Rate with Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Antoniou:2010:AIAI,
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author = "Maria Antoniou and Efstratios Georgopoulos and
Konstantinos Theofilatos and Spiridon Likothanassis",
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title = "Forecasting Euro - United States Dollar Exchange Rate
with Gene Expression Programming",
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booktitle = "6th IFIP Advances in Information and Communication
Technology AIAI 2010",
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year = "2010",
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editor = "Harris Papadopoulos and Andreas Andreou and
Max Bramer",
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volume = "339",
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series = "IFIP Advances in Information and Communication
Technology",
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pages = "78--85",
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address = "Larnaca, Cyprus",
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month = oct # " 6-7",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Gene
Expression Programming",
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DOI = "doi:10.1007/978-3-642-16239-8_13",
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abstract = "In the current paper we present the application of our
Gene Expression Programming Environment in forecasting
Euro-United States Dollar exchange rate. Specifically,
using the GEP Environment we tried to forecast the
value of the exchange rate using its previous values.
The data for the EURO-USD exchange rate are online
available from the European Central Bank (ECB). The
environment was developed using the JAVA programming
language, and is an implementation of a variation of
Gene Expression Programming. Gene Expression
Programming (GEP) is a new evolutionary algorithm that
evolves computer programs (they can take many forms:
mathematical expressions, neural networks, decision
trees, polynomial constructs, logical expressions, and
so on). The computer programs of GEP, irrespective of
their complexity, are all encoded in linear
chromosomes. Then the linear chromosomes are expressed
or translated into expression trees (branched
structures). Thus, in GEP, the genotype (the linear
chromosomes) and the phenotype (the expression trees)
are different entities (both structurally and
functionally). This is the main difference between GEP
and classical tree based Genetic Programming
techniques.",
-
affiliation = "Pattern Recognition Laboratory, Dept. of Computer
Engineering & Informatics, University of Patras, 26500
Patras, Greece",
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notes = "http://www.cs.ucy.ac.cy/aiai2010/",
- }
Genetic Programming entries for
Maria A Antoniou
Efstratios F Georgopoulos
Konstantinos A Theofilatos
Spiridon D Likothanassis
Citations