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dc.contributor.authorMuhammad Fuad, Muhammad Marwan
dc.date.accessioned2014-03-05T08:57:09Z
dc.date.available2014-03-05T08:57:09Z
dc.date.issued2013
dc.description.abstractBio-inspired optimization algorithms have been successfully applied to solve many problems in engineering, science, and economics. In computer science bio-inspired optimization has different applications in different domains such as software engineering, networks, data mining, and many others. However, some applications may not be appropriate or even correct. In this paper we study this phenomenon through a particular method which applies the genetic algorithms on a time series classification task to set the weights of the similarity measures used in a combination that is used to classify the time series. The weights are supposed to be obtained by applying an optimization process that gives optimal classification accuracy. We show in this work, through examples, discussions, remarks, explanations, and experiments, that the aforementioned method of optimization is not correct and that completely randomly-chosen weights for the similarity measures can give the same classification accuracy.en
dc.identifier.citationLecture Notes in Computer Science 8346(2013) s. 121-132en
dc.identifier.cristinIDFRIDAID 1115862
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-642-53914-5_11
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/10037/5910
dc.identifier.urnURN:NBN:no-uit_munin_5601
dc.language.isoengen
dc.publisherSpringer Verlagen
dc.rights.accessRightsopenAccess
dc.subjectVDP::Mathematics and natural science: 400::Chemistry: 440::Theoretical chemistry, quantum chemistry: 444en
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Kjemi: 440::Teoretisk kjemi, kvantekjemi: 444en
dc.subjectVDP::Mathematics and natural science: 400::Mathematics: 410en
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410en
dc.titleWhen Optimization Is Just an Illusionen
dc.typeJournal articleen
dc.typeTidsskriftartikkelen
dc.typePeer revieweden


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