Forecasting Euro - United States Dollar Exchange Rate with Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Antoniou:2010:AIAI,

• author = "Maria Antoniou and Efstratios Georgopoulos and Konstantinos Theofilatos and Spiridon Likothanassis",
• title = "Forecasting Euro - United States Dollar Exchange Rate with Gene Expression Programming",
• booktitle = "6th IFIP Advances in Information and Communication Technology AIAI 2010",
• year = "2010",
• editor = "Harris Papadopoulos and Andreas Andreou and Max Bramer",
• volume = "339",
• series = "IFIP Advances in Information and Communication Technology",
• pages = "78--85",
• address = "Larnaca, Cyprus",
• month = oct # " 6-7",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Gene Expression Programming",
• DOI = "doi:10.1007/978-3-642-16239-8_13",
• 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",
• 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