Bayesian modeling and optimization for multi-response surfaces
• Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quali...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Jianjun [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling - Zhang, Chuang ELSEVIER, 2018, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:142 ; year:2020 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.cie.2020.106357 |
|---|
| Katalog-ID: |
ELV049926810 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV049926810 | ||
| 003 | DE-627 | ||
| 005 | 20230624160550.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 200518s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.cie.2020.106357 |2 doi | |
| 028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica |
| 035 | |a (DE-627)ELV049926810 | ||
| 035 | |a (ELSEVIER)S0360-8352(20)30091-7 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 630 |a 640 |q VZ |
| 084 | |a 58.34 |2 bkl | ||
| 100 | 1 | |a Wang, Jianjun |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Bayesian modeling and optimization for multi-response surfaces |
| 264 | 1 | |c 2020 | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a • Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. | ||
| 650 | 7 | |a Seemingly unrelated regression |2 Elsevier | |
| 650 | 7 | |a Conformance probability |2 Elsevier | |
| 650 | 7 | |a Quality loss function |2 Elsevier | |
| 650 | 7 | |a Bayesian analysis |2 Elsevier | |
| 650 | 7 | |a Model parameter uncertainty |2 Elsevier | |
| 650 | 7 | |a Multi-response optimization |2 Elsevier | |
| 700 | 1 | |a Ma, Yizhong |4 oth | |
| 700 | 1 | |a Ouyang, Linhan |4 oth | |
| 700 | 1 | |a Tu, Yiliu |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Zhang, Chuang ELSEVIER |t Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling |d 2018 |g Amsterdam [u.a.] |w (DE-627)ELV00175033X |
| 773 | 1 | 8 | |g volume:142 |g year:2020 |g pages:0 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.cie.2020.106357 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 936 | b | k | |a 58.34 |j Lebensmitteltechnologie |q VZ |
| 951 | |a AR | ||
| 952 | |d 142 |j 2020 |h 0 | ||
| author_variant |
j w jw |
|---|---|
| matchkey_str |
wangjianjunmayizhongouyanglinhantuyiliu:2020----:aeinoeignotmztofrut |
| hierarchy_sort_str |
2020 |
| bklnumber |
58.34 |
| publishDate |
2020 |
| allfields |
10.1016/j.cie.2020.106357 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica (DE-627)ELV049926810 (ELSEVIER)S0360-8352(20)30091-7 DE-627 ger DE-627 rakwb eng 630 640 VZ 58.34 bkl Wang, Jianjun verfasserin aut Bayesian modeling and optimization for multi-response surfaces 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Elsevier Ma, Yizhong oth Ouyang, Linhan oth Tu, Yiliu oth Enthalten in Elsevier Science Zhang, Chuang ELSEVIER Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling 2018 Amsterdam [u.a.] (DE-627)ELV00175033X volume:142 year:2020 pages:0 https://doi.org/10.1016/j.cie.2020.106357 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 58.34 Lebensmitteltechnologie VZ AR 142 2020 0 |
| spelling |
10.1016/j.cie.2020.106357 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica (DE-627)ELV049926810 (ELSEVIER)S0360-8352(20)30091-7 DE-627 ger DE-627 rakwb eng 630 640 VZ 58.34 bkl Wang, Jianjun verfasserin aut Bayesian modeling and optimization for multi-response surfaces 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Elsevier Ma, Yizhong oth Ouyang, Linhan oth Tu, Yiliu oth Enthalten in Elsevier Science Zhang, Chuang ELSEVIER Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling 2018 Amsterdam [u.a.] (DE-627)ELV00175033X volume:142 year:2020 pages:0 https://doi.org/10.1016/j.cie.2020.106357 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 58.34 Lebensmitteltechnologie VZ AR 142 2020 0 |
| allfields_unstemmed |
10.1016/j.cie.2020.106357 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica (DE-627)ELV049926810 (ELSEVIER)S0360-8352(20)30091-7 DE-627 ger DE-627 rakwb eng 630 640 VZ 58.34 bkl Wang, Jianjun verfasserin aut Bayesian modeling and optimization for multi-response surfaces 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Elsevier Ma, Yizhong oth Ouyang, Linhan oth Tu, Yiliu oth Enthalten in Elsevier Science Zhang, Chuang ELSEVIER Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling 2018 Amsterdam [u.a.] (DE-627)ELV00175033X volume:142 year:2020 pages:0 https://doi.org/10.1016/j.cie.2020.106357 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 58.34 Lebensmitteltechnologie VZ AR 142 2020 0 |
| allfieldsGer |
10.1016/j.cie.2020.106357 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica (DE-627)ELV049926810 (ELSEVIER)S0360-8352(20)30091-7 DE-627 ger DE-627 rakwb eng 630 640 VZ 58.34 bkl Wang, Jianjun verfasserin aut Bayesian modeling and optimization for multi-response surfaces 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Elsevier Ma, Yizhong oth Ouyang, Linhan oth Tu, Yiliu oth Enthalten in Elsevier Science Zhang, Chuang ELSEVIER Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling 2018 Amsterdam [u.a.] (DE-627)ELV00175033X volume:142 year:2020 pages:0 https://doi.org/10.1016/j.cie.2020.106357 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 58.34 Lebensmitteltechnologie VZ AR 142 2020 0 |
| allfieldsSound |
10.1016/j.cie.2020.106357 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica (DE-627)ELV049926810 (ELSEVIER)S0360-8352(20)30091-7 DE-627 ger DE-627 rakwb eng 630 640 VZ 58.34 bkl Wang, Jianjun verfasserin aut Bayesian modeling and optimization for multi-response surfaces 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Elsevier Ma, Yizhong oth Ouyang, Linhan oth Tu, Yiliu oth Enthalten in Elsevier Science Zhang, Chuang ELSEVIER Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling 2018 Amsterdam [u.a.] (DE-627)ELV00175033X volume:142 year:2020 pages:0 https://doi.org/10.1016/j.cie.2020.106357 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 58.34 Lebensmitteltechnologie VZ AR 142 2020 0 |
| language |
English |
| source |
Enthalten in Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling Amsterdam [u.a.] volume:142 year:2020 pages:0 |
| sourceStr |
Enthalten in Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling Amsterdam [u.a.] volume:142 year:2020 pages:0 |
| format_phy_str_mv |
Article |
| bklname |
Lebensmitteltechnologie |
| institution |
findex.gbv.de |
| topic_facet |
Seemingly unrelated regression Conformance probability Quality loss function Bayesian analysis Model parameter uncertainty Multi-response optimization |
| dewey-raw |
630 |
| isfreeaccess_bool |
false |
| container_title |
Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling |
| authorswithroles_txt_mv |
Wang, Jianjun @@aut@@ Ma, Yizhong @@oth@@ Ouyang, Linhan @@oth@@ Tu, Yiliu @@oth@@ |
| publishDateDaySort_date |
2020-01-01T00:00:00Z |
| hierarchy_top_id |
ELV00175033X |
| dewey-sort |
3630 |
| id |
ELV049926810 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV049926810</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624160550.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200518s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.cie.2020.106357</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV049926810</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0360-8352(20)30091-7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="a">640</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">58.34</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wang, Jianjun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bayesian modeling and optimization for multi-response surfaces</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Seemingly unrelated regression</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Conformance probability</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Quality loss function</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Bayesian analysis</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Model parameter uncertainty</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Multi-response optimization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ma, Yizhong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ouyang, Linhan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tu, Yiliu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Zhang, Chuang ELSEVIER</subfield><subfield code="t">Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling</subfield><subfield code="d">2018</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV00175033X</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:142</subfield><subfield code="g">year:2020</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.cie.2020.106357</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">58.34</subfield><subfield code="j">Lebensmitteltechnologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">142</subfield><subfield code="j">2020</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| author |
Wang, Jianjun |
| spellingShingle |
Wang, Jianjun ddc 630 bkl 58.34 Elsevier Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Bayesian modeling and optimization for multi-response surfaces |
| authorStr |
Wang, Jianjun |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV00175033X |
| format |
electronic Article |
| dewey-ones |
630 - Agriculture & related technologies 640 - Home & family management |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
630 640 VZ 58.34 bkl Bayesian modeling and optimization for multi-response surfaces Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization Elsevier |
| topic |
ddc 630 bkl 58.34 Elsevier Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization |
| topic_unstemmed |
ddc 630 bkl 58.34 Elsevier Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization |
| topic_browse |
ddc 630 bkl 58.34 Elsevier Seemingly unrelated regression Elsevier Conformance probability Elsevier Quality loss function Elsevier Bayesian analysis Elsevier Model parameter uncertainty Elsevier Multi-response optimization |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
y m ym l o lo y t yt |
| hierarchy_parent_title |
Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling |
| hierarchy_parent_id |
ELV00175033X |
| dewey-tens |
630 - Agriculture 640 - Home & family management |
| hierarchy_top_title |
Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV00175033X |
| title |
Bayesian modeling and optimization for multi-response surfaces |
| ctrlnum |
(DE-627)ELV049926810 (ELSEVIER)S0360-8352(20)30091-7 |
| title_full |
Bayesian modeling and optimization for multi-response surfaces |
| author_sort |
Wang, Jianjun |
| journal |
Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling |
| journalStr |
Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
zzz |
| container_start_page |
0 |
| author_browse |
Wang, Jianjun |
| container_volume |
142 |
| class |
630 640 VZ 58.34 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Wang, Jianjun |
| doi_str_mv |
10.1016/j.cie.2020.106357 |
| dewey-full |
630 640 |
| title_sort |
bayesian modeling and optimization for multi-response surfaces |
| title_auth |
Bayesian modeling and optimization for multi-response surfaces |
| abstract |
• Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. |
| abstractGer |
• Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. |
| abstract_unstemmed |
• Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U |
| title_short |
Bayesian modeling and optimization for multi-response surfaces |
| url |
https://doi.org/10.1016/j.cie.2020.106357 |
| remote_bool |
true |
| author2 |
Ma, Yizhong Ouyang, Linhan Tu, Yiliu |
| author2Str |
Ma, Yizhong Ouyang, Linhan Tu, Yiliu |
| ppnlink |
ELV00175033X |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth |
| doi_str |
10.1016/j.cie.2020.106357 |
| up_date |
2024-07-06T22:55:23.189Z |
| _version_ |
1803872132861526016 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV049926810</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624160550.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200518s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.cie.2020.106357</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001142.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV049926810</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0360-8352(20)30091-7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="a">640</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">58.34</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wang, Jianjun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bayesian modeling and optimization for multi-response surfaces</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• Integrating quality loss with conformance probability. • Conformance probability can be obtained by using posterior samplers. • Compare optimization results between Bayesian SMR and SUR modeling. • Both parameter uncertainty and response variability are considered. • Make a trade-off between quality loss and conformance probability.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Seemingly unrelated regression</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Conformance probability</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Quality loss function</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Bayesian analysis</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Model parameter uncertainty</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Multi-response optimization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ma, Yizhong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ouyang, Linhan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tu, Yiliu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Zhang, Chuang ELSEVIER</subfield><subfield code="t">Exploring the drying behaviors of microencapsulated noni juice using reaction engineering approach (REA) mathematical modelling</subfield><subfield code="d">2018</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV00175033X</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:142</subfield><subfield code="g">year:2020</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.cie.2020.106357</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">58.34</subfield><subfield code="j">Lebensmitteltechnologie</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">142</subfield><subfield code="j">2020</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| score |
7.399147 |