The Gene Expression Programming Applied to Demand Forecast
Created by W.Langdon from
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- @InProceedings{conf/softcomp/BittencourtSLAO10,
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author = "Evandro Bittencourt and Sidney Schossland and
Raul Landmann and Denio {Murilo de Aguiar} and
Adilson Gomes {De Oliveira}",
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title = "The Gene Expression Programming Applied to Demand
Forecast",
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booktitle = "Soft Computing Models in Industrial and Environmental
Applications, 5th International Workshop (SOCO 2010)",
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year = "2010",
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editor = "Emilio Corchado and Paulo Novais and Cesar Analide and
Javier Sedano",
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volume = "73",
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series = "Advances in Intelligent and Soft Computing",
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pages = "197--200",
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address = "Guimaraes, Portugal",
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month = jun,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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isbn13 = "978-3-642-13160-8",
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DOI = "doi:10.1007/978-3-642-13161-5_25",
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abstract = "This paper examines the use of artificial intelligence
(in particular the application of Gene Expression
Programming, GEP) to demand forecasting. In the world
of production management, many data that are produced
in function of the of economic activity characteristics
in which they belong, may suffer, for example,
significant impacts of seasonal behaviours, making the
prediction of future conditions difficult by means of
methods commonly used. The GEP is an evolution of
Genetic Programming,which is part of the Genetic
Algorithms. GEP seeks for mathematical functions,
adjusting to a given set of solutions using a type of
genetic heuristics from a population of random
functions. In order to compare the GEP, we have used
the others quantitatives method. Thus, from a data set
of about demand of consumption of twelve products line
metal fittings, we have compared the forecast data.",
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bibdate = "2010-11-04",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/softcomp/soco2010.html#BittencourtSLAO10",
- }
Genetic Programming entries for
Evandro Bittencourt
Sidney Schossland
Raul Landmann
Denio Murilo de Aguiar
Adilson Gomes De Oliveira
Citations