Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Beielstein, Thomas | de |
dc.contributor.author | Markon, Sandor | de |
dc.date.accessioned | 2004-12-07T08:21:00Z | - |
dc.date.available | 2004-12-07T08:21:00Z | - |
dc.date.created | 2001 | de |
dc.date.issued | 2002-04-08 | de |
dc.identifier.uri | http://hdl.handle.net/2003/5417 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-15303 | - |
dc.description.abstract | Threshold 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.extent | 303878 bytes | - |
dc.format.extent | 331954 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/postscript | - |
dc.language.iso | en | de |
dc.publisher | Universität Dortmund | de |
dc.relation.ispartofseries | Reihe Computational Intelligence ; 121 | de |
dc.subject.ddc | 004 | de |
dc.title | Threshold Selection, Hypothesis Tests, and DOE Methods | en |
dc.type | Text | de |
dc.type.publicationtype | report | - |
dcterms.accessRights | open access | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 531 |
Files in This Item:
File | Description | Size | Format | |
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121.pdf | DNB | 324.17 kB | Adobe PDF | View/Open |
121.ps | 296.76 kB | Postscript | View/Open |
This item is protected by original copyright |
This item is protected by original copyright
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