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dc.contributor.authorBeielstein, Thomasde
dc.contributor.authorMarkon, Sandorde
dc.date.accessioned2004-12-07T08:21:00Z-
dc.date.available2004-12-07T08:21:00Z-
dc.date.created2001de
dc.date.issued2002-04-08de
dc.identifier.urihttp://hdl.handle.net/2003/5417-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15303-
dc.description.abstractThreshold selection - a selection mechanism for noisy evolutionary algorithms - is put into the broader context of hypothesis testing. Theoretical results are presented and applied to a simple model of stochastic search and to a simplified elevator simulator. Design of experiments methods are used to validate the significance of the results.en
dc.format.extent303878 bytes-
dc.format.extent331954 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesReihe Computational Intelligence ; 121de
dc.subject.ddc004de
dc.titleThreshold Selection, Hypothesis Tests, and DOE Methodsen
dc.typeTextde
dc.type.publicationtypereport-
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 531

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