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DCフィールド | 値 | 言語 |
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dc.contributor.author | Fujiwara, Koichi | en |
dc.contributor.author | Kano, Manabu | en |
dc.contributor.alternative | 藤原, 幸一 | ja |
dc.date.accessioned | 2016-02-01T05:48:44Z | - |
dc.date.available | 2016-02-01T05:48:44Z | - |
dc.date.issued | 2015-09 | - |
dc.identifier.issn | 0019-0578 | - |
dc.identifier.uri | http://hdl.handle.net/2433/203543 | - |
dc.description.abstract | Appropriate input variables have to be selected for building highly accurate soft sensor. A novel input variable selection method based on nearest correlation spectral clustering (NCSC) has been proposed, and it is referred to as NCSC-based variable selection (NCSC-VS). Although NCSC-VS can select appropriate input variables, a lot of parameters have to be tuned carefully for selecting proper variables. The present work proposes a new methodology for efficient input variable selection by integrating NCSC and group Lasso. The proposed NCSC-based group Lasso (NCSC-GL) can not only reduce the number of tuning parameters but also achieve almost the same performance as NCSC-VS. The usefulness of the proposed NCSC-GL is demonstrated through applications to soft sensor design for a pharmaceutical process and a chemical process. | en |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Elsevier Ltd. | en |
dc.rights | © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
dc.rights | The full-text file will be made open to the public on 1 September 2017 in accordance with publisher's 'Terms and Conditions for Self-Archiving'. | en |
dc.rights | この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 | ja |
dc.rights | This is not the published version. Please cite only the published version. | en |
dc.subject | Soft-sensor design | en |
dc.subject | Input variable selection | en |
dc.subject | Group Lasso | en |
dc.subject | Spectral clustering | en |
dc.subject | Near infrared spectroscopy | en |
dc.title | Efficient input variable selection for soft-senor design based on nearest correlation spectral clustering and group Lasso | en |
dc.type | journal article | - |
dc.type.niitype | Journal Article | - |
dc.identifier.ncid | AA00669225 | - |
dc.identifier.jtitle | ISA Transactions | en |
dc.identifier.volume | 58 | - |
dc.identifier.spage | 367 | - |
dc.identifier.epage | 379 | - |
dc.relation.doi | 10.1016/j.isatra.2015.04.007 | - |
dc.textversion | author | - |
dc.startdate.bitstreamsavailable | 2017-09-01 | - |
dcterms.accessRights | open access | - |
出現コレクション: | 学術雑誌掲載論文等 |
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