A hybrid model of partial least squares and artificial neural network for analyzing process monitoring data
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, YS | ko |
| dc.contributor.author | Yum, Bong-Jin | ko |
| dc.contributor.author | Kim, M | ko |
| dc.date.accessioned | 2013-03-15T23:48:21Z | - |
| dc.date.available | 2013-03-15T23:48:21Z | - |
| dc.date.created | 2012-02-06 | - |
| dc.date.created | 2012-02-06 | - |
| dc.date.issued | 2001-07-15 | - |
| dc.identifier.citation | International Joint Conference on Neural Networks (IJCNN'01), pp.2292 - 2297 | - |
| dc.identifier.uri | http://hdl.handle.net/10203/125232 | - |
| dc.language | English | - |
| dc.publisher | IJCNN | - |
| dc.title | A hybrid model of partial least squares and artificial neural network for analyzing process monitoring data | - |
| dc.type | Conference | - |
| dc.identifier.wosid | 000172784800407 | - |
| dc.identifier.scopusid | 2-s2.0-0034862223 | - |
| dc.type.rims | CONF | - |
| dc.citation.beginningpage | 2292 | - |
| dc.citation.endingpage | 2297 | - |
| dc.citation.publicationname | International Joint Conference on Neural Networks (IJCNN'01) | - |
| dc.identifier.conferencecountry | US | - |
| dc.identifier.conferencelocation | Washington, DC | - |
| dc.contributor.localauthor | Yum, Bong-Jin | - |
| dc.contributor.nonIdAuthor | Kim, YS | - |
| dc.contributor.nonIdAuthor | Kim, M | - |
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