Ridge Path in Mixtures Experiments: Optimal Result with Restriction on Prediction of Variance

In order to evaluate a methodology applied to the ridge analysis in mixing experiments with linear constraints, this article proposes through the construction of a ridge path to obtain the maximum or minimum value of the predicted response under a prediction variance conditioned to a restriction. Fo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Revista IEEE América Latina 2017-02, Vol.15 (2), p.290-299
Hauptverfasser: Nepomucena, Tania Miranda, Cirillo, Marcelo Angelo, Menezes, Fortunato Silva
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 299
container_issue 2
container_start_page 290
container_title Revista IEEE América Latina
container_volume 15
creator Nepomucena, Tania Miranda
Cirillo, Marcelo Angelo
Menezes, Fortunato Silva
description In order to evaluate a methodology applied to the ridge analysis in mixing experiments with linear constraints, this article proposes through the construction of a ridge path to obtain the maximum or minimum value of the predicted response under a prediction variance conditioned to a restriction. For this purpose, we considered two experiments mixtures with variables with a lower or upper bound limit. The results were compared with the ones obtained by other methods available in the literature in industrial application. According to the degree of multicollinearity of the variables in each experiment, it was observed that the proposed methodology was efficient to provide predicted response with the value higher than the maximum obtained by existing methods and variance reduced prediction
doi_str_mv 10.1109/TLA.2017.7854625
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TLA_2017_7854625</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7854625</ieee_id><sourcerecordid>1869421262</sourcerecordid><originalsourceid>FETCH-LOGICAL-c221t-aa8bc312601c30048e2985815b7ea22e175994ce468307b78c2b3a05e4a20ca13</originalsourceid><addsrcrecordid>eNpNUE1LAzEQDaJgrd4FLwHPuybZZDfrrZT6AZWWUr1JyKZTTWl31ySL9d-b0laEgZlh3rx58xC6piSllJR38_EgZYQWaSEFz5k4QT0quExIWbLTf_U5uvB-RUgmc5n10PvMLj4AT3X4xLbGL3YbOgcej7YtOLuBOvh7PGmD3eg1noHv1gF_2wiOdXDWBNvUOMbUweLYLfGbdlbXBi7R2VKvPVwdch-9Pozmw6dkPHl8Hg7GiWGMhkRrWZmMspxQkxHCJbBSCklFVYBmDGghypIb4FEyKapCGlZlmgjgmhGjadZHt3ve1jVfXVSmVk3n6nhSUZmXnEVuFlFkjzKu8d7BUrXxRe1-FCVqZ6KKJqqdiepgYly52a9YAPiDH6e_OPVs1A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1869421262</pqid></control><display><type>article</type><title>Ridge Path in Mixtures Experiments: Optimal Result with Restriction on Prediction of Variance</title><source>IEEE Electronic Library (IEL)</source><creator>Nepomucena, Tania Miranda ; Cirillo, Marcelo Angelo ; Menezes, Fortunato Silva</creator><creatorcontrib>Nepomucena, Tania Miranda ; Cirillo, Marcelo Angelo ; Menezes, Fortunato Silva</creatorcontrib><description>In order to evaluate a methodology applied to the ridge analysis in mixing experiments with linear constraints, this article proposes through the construction of a ridge path to obtain the maximum or minimum value of the predicted response under a prediction variance conditioned to a restriction. For this purpose, we considered two experiments mixtures with variables with a lower or upper bound limit. The results were compared with the ones obtained by other methods available in the literature in industrial application. According to the degree of multicollinearity of the variables in each experiment, it was observed that the proposed methodology was efficient to provide predicted response with the value higher than the maximum obtained by existing methods and variance reduced prediction</description><identifier>ISSN: 1548-0992</identifier><identifier>EISSN: 1548-0992</identifier><identifier>DOI: 10.1109/TLA.2017.7854625</identifier><language>eng</language><publisher>Los Alamitos: IEEE</publisher><subject>Adaptation models ; Computational modeling ; IEEE transactions ; Industrial applications ; Matrix decomposition ; Mixtures ; Monitoring ; Multicolinearity ; Optimization ; Predicition Variance ; Predictions ; Reactive power ; Upper bound ; Upper bounds ; Variance</subject><ispartof>Revista IEEE América Latina, 2017-02, Vol.15 (2), p.290-299</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c221t-aa8bc312601c30048e2985815b7ea22e175994ce468307b78c2b3a05e4a20ca13</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7854625$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7854625$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Nepomucena, Tania Miranda</creatorcontrib><creatorcontrib>Cirillo, Marcelo Angelo</creatorcontrib><creatorcontrib>Menezes, Fortunato Silva</creatorcontrib><title>Ridge Path in Mixtures Experiments: Optimal Result with Restriction on Prediction of Variance</title><title>Revista IEEE América Latina</title><addtitle>T-LA</addtitle><description>In order to evaluate a methodology applied to the ridge analysis in mixing experiments with linear constraints, this article proposes through the construction of a ridge path to obtain the maximum or minimum value of the predicted response under a prediction variance conditioned to a restriction. For this purpose, we considered two experiments mixtures with variables with a lower or upper bound limit. The results were compared with the ones obtained by other methods available in the literature in industrial application. According to the degree of multicollinearity of the variables in each experiment, it was observed that the proposed methodology was efficient to provide predicted response with the value higher than the maximum obtained by existing methods and variance reduced prediction</description><subject>Adaptation models</subject><subject>Computational modeling</subject><subject>IEEE transactions</subject><subject>Industrial applications</subject><subject>Matrix decomposition</subject><subject>Mixtures</subject><subject>Monitoring</subject><subject>Multicolinearity</subject><subject>Optimization</subject><subject>Predicition Variance</subject><subject>Predictions</subject><subject>Reactive power</subject><subject>Upper bound</subject><subject>Upper bounds</subject><subject>Variance</subject><issn>1548-0992</issn><issn>1548-0992</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNUE1LAzEQDaJgrd4FLwHPuybZZDfrrZT6AZWWUr1JyKZTTWl31ySL9d-b0laEgZlh3rx58xC6piSllJR38_EgZYQWaSEFz5k4QT0quExIWbLTf_U5uvB-RUgmc5n10PvMLj4AT3X4xLbGL3YbOgcej7YtOLuBOvh7PGmD3eg1noHv1gF_2wiOdXDWBNvUOMbUweLYLfGbdlbXBi7R2VKvPVwdch-9Pozmw6dkPHl8Hg7GiWGMhkRrWZmMspxQkxHCJbBSCklFVYBmDGghypIb4FEyKapCGlZlmgjgmhGjadZHt3ve1jVfXVSmVk3n6nhSUZmXnEVuFlFkjzKu8d7BUrXxRe1-FCVqZ6KKJqqdiepgYly52a9YAPiDH6e_OPVs1A</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Nepomucena, Tania Miranda</creator><creator>Cirillo, Marcelo Angelo</creator><creator>Menezes, Fortunato Silva</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20170201</creationdate><title>Ridge Path in Mixtures Experiments: Optimal Result with Restriction on Prediction of Variance</title><author>Nepomucena, Tania Miranda ; Cirillo, Marcelo Angelo ; Menezes, Fortunato Silva</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c221t-aa8bc312601c30048e2985815b7ea22e175994ce468307b78c2b3a05e4a20ca13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adaptation models</topic><topic>Computational modeling</topic><topic>IEEE transactions</topic><topic>Industrial applications</topic><topic>Matrix decomposition</topic><topic>Mixtures</topic><topic>Monitoring</topic><topic>Multicolinearity</topic><topic>Optimization</topic><topic>Predicition Variance</topic><topic>Predictions</topic><topic>Reactive power</topic><topic>Upper bound</topic><topic>Upper bounds</topic><topic>Variance</topic><toplevel>online_resources</toplevel><creatorcontrib>Nepomucena, Tania Miranda</creatorcontrib><creatorcontrib>Cirillo, Marcelo Angelo</creatorcontrib><creatorcontrib>Menezes, Fortunato Silva</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Revista IEEE América Latina</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Nepomucena, Tania Miranda</au><au>Cirillo, Marcelo Angelo</au><au>Menezes, Fortunato Silva</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ridge Path in Mixtures Experiments: Optimal Result with Restriction on Prediction of Variance</atitle><jtitle>Revista IEEE América Latina</jtitle><stitle>T-LA</stitle><date>2017-02-01</date><risdate>2017</risdate><volume>15</volume><issue>2</issue><spage>290</spage><epage>299</epage><pages>290-299</pages><issn>1548-0992</issn><eissn>1548-0992</eissn><abstract>In order to evaluate a methodology applied to the ridge analysis in mixing experiments with linear constraints, this article proposes through the construction of a ridge path to obtain the maximum or minimum value of the predicted response under a prediction variance conditioned to a restriction. For this purpose, we considered two experiments mixtures with variables with a lower or upper bound limit. The results were compared with the ones obtained by other methods available in the literature in industrial application. According to the degree of multicollinearity of the variables in each experiment, it was observed that the proposed methodology was efficient to provide predicted response with the value higher than the maximum obtained by existing methods and variance reduced prediction</abstract><cop>Los Alamitos</cop><pub>IEEE</pub><doi>10.1109/TLA.2017.7854625</doi><tpages>10</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1548-0992
ispartof Revista IEEE América Latina, 2017-02, Vol.15 (2), p.290-299
issn 1548-0992
1548-0992
language eng
recordid cdi_crossref_primary_10_1109_TLA_2017_7854625
source IEEE Electronic Library (IEL)
subjects Adaptation models
Computational modeling
IEEE transactions
Industrial applications
Matrix decomposition
Mixtures
Monitoring
Multicolinearity
Optimization
Predicition Variance
Predictions
Reactive power
Upper bound
Upper bounds
Variance
title Ridge Path in Mixtures Experiments: Optimal Result with Restriction on Prediction of Variance
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T05%3A49%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Ridge%20Path%20in%20Mixtures%20Experiments:%20Optimal%20Result%20with%20Restriction%20on%20Prediction%20of%20Variance&rft.jtitle=Revista%20IEEE%20Am%C3%A9rica%20Latina&rft.au=Nepomucena,%20Tania%20Miranda&rft.date=2017-02-01&rft.volume=15&rft.issue=2&rft.spage=290&rft.epage=299&rft.pages=290-299&rft.issn=1548-0992&rft.eissn=1548-0992&rft_id=info:doi/10.1109/TLA.2017.7854625&rft_dat=%3Cproquest_RIE%3E1869421262%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1869421262&rft_id=info:pmid/&rft_ieee_id=7854625&rfr_iscdi=true