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dc.contributor.authorFoster, Ernest Allen
dc.date.accessioned2014-03-03T20:19:45Z
dc.date.available2014-03-03T20:19:45Z
dc.date.issued2002-12
dc.identifier.otherfoster_ernest_a_200212_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/foster_ernest_a_200212_ms
dc.identifier.urihttp://hdl.handle.net/10724/20557
dc.description.abstractThis thesis describes an attempt to predict the next value in a .nancial time series using various arti .cial techniques.The time series in question consists of daily values for commodities futures.First,an arti .cial neural network is used as a pre- dictor.Then the neural network is augmented with a genetic algorithm.The genetic algorithm .rst is used to select the parameters for the neural network.Then in a seperate experiment the genetic algorithm is used to evolve the weights of the network.The various approaches had similar results.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectartificial neural networks
dc.subjectgenetic algorithms
dc.subjectcommodity futures
dc.subjecttime series analysis
dc.titleCommodity futures price prediction : an artificial intelligence approach
dc.typeThesis
dc.description.degreeMS
dc.description.departmentArtificial Intelligence
dc.description.majorArtificial Intelligence
dc.description.advisorWalter D. Potter
dc.description.committeeWalter D. Potter
dc.description.committeeDonald Nute
dc.description.committeeKhaled Rasheed


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