Prediction of the mechanical properties of hot-rolled C-Mn steels by single index model
Semi-parametric single index model based approach is proposed for prediction of mechanical properties of hot rolled strip in this paper. Based on industrial production data, a semi-parametric single index model is developed by choosing the appropriate kernel function and window width to predict the...
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| creator | Yang Weng Yonghong Zhao Guangbo Tang Zhengdong Liu |
| description | Semi-parametric single index model based approach is proposed for prediction of mechanical properties of hot rolled strip in this paper. Based on industrial production data, a semi-parametric single index model is developed by choosing the appropriate kernel function and window width to predict the yield strength, tensile strength and elongation. When data samples are limited, compared with regression method and neural network method, the prediction results show that the semi-parametric single-index model based method is more adaptive and the prediction performance is superior to both regression and neural network methods. |
| doi_str_mv | 10.1109/ICCSE.2013.6553924 |
| format | Conference Proceeding |
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Based on industrial production data, a semi-parametric single index model is developed by choosing the appropriate kernel function and window width to predict the yield strength, tensile strength and elongation. When data samples are limited, compared with regression method and neural network method, the prediction results show that the semi-parametric single-index model based method is more adaptive and the prediction performance is superior to both regression and neural network methods.</description><identifier>ISBN: 1467344648</identifier><identifier>ISBN: 9781467344647</identifier><identifier>EISBN: 1467344621</identifier><identifier>EISBN: 9781467344630</identifier><identifier>EISBN: 146734463X</identifier><identifier>EISBN: 9781467344623</identifier><identifier>DOI: 10.1109/ICCSE.2013.6553924</identifier><language>eng</language><publisher>IEEE</publisher><subject>Computers ; hot strip rolling ; Indexes ; Mechanical factors ; mechanical property prediction ; neural network ; Nickel ; regression analysis ; semi-parametric single-index model</subject><ispartof>2013 8th International Conference on Computer Science & Education, 2013, p.275-280</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6553924$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6553924$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yang Weng</creatorcontrib><creatorcontrib>Yonghong Zhao</creatorcontrib><creatorcontrib>Guangbo Tang</creatorcontrib><creatorcontrib>Zhengdong Liu</creatorcontrib><title>Prediction of the mechanical properties of hot-rolled C-Mn steels by single index model</title><title>2013 8th International Conference on Computer Science & Education</title><addtitle>ICCSE</addtitle><description>Semi-parametric single index model based approach is proposed for prediction of mechanical properties of hot rolled strip in this paper. Based on industrial production data, a semi-parametric single index model is developed by choosing the appropriate kernel function and window width to predict the yield strength, tensile strength and elongation. When data samples are limited, compared with regression method and neural network method, the prediction results show that the semi-parametric single-index model based method is more adaptive and the prediction performance is superior to both regression and neural network methods.</description><subject>Computers</subject><subject>hot strip rolling</subject><subject>Indexes</subject><subject>Mechanical factors</subject><subject>mechanical property prediction</subject><subject>neural network</subject><subject>Nickel</subject><subject>regression analysis</subject><subject>semi-parametric single-index model</subject><isbn>1467344648</isbn><isbn>9781467344647</isbn><isbn>1467344621</isbn><isbn>9781467344630</isbn><isbn>146734463X</isbn><isbn>9781467344623</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkMFKxDAURSMiqOP8gG7yA615SZO0SymjMzCioOJySJMXG0nbIenC-XsVB1xdLod7FpeQa2AlAGtuN237sio5A1EqKUXDqxNyCZXSoqoUh9P_UtXnZJnzJ2PsZ6l0DRfk_TmhC3YO00gnT-ce6YC2N2OwJtJ9mvaY5oD5F_bTXKQpRnS0LR5HmmfEmGl3oDmMHxFpGB1-0WFyGK_ImTcx4_KYC_J2v3pt18X26WHT3m2LAFrOhfc1Wu-cVYhcWt6hByF4LaFRneCNA8u00BKZklAZ16BmndVgDVhEj2JBbv68ARF3-xQGkw674xHiG5f_UyM</recordid><startdate>201304</startdate><enddate>201304</enddate><creator>Yang Weng</creator><creator>Yonghong Zhao</creator><creator>Guangbo Tang</creator><creator>Zhengdong Liu</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201304</creationdate><title>Prediction of the mechanical properties of hot-rolled C-Mn steels by single index model</title><author>Yang Weng ; Yonghong Zhao ; Guangbo Tang ; Zhengdong Liu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-ff8ecfddc6ee25c2bef133285196b329d1c07375e06514ad9e70bc71ca1ceefe3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Computers</topic><topic>hot strip rolling</topic><topic>Indexes</topic><topic>Mechanical factors</topic><topic>mechanical property prediction</topic><topic>neural network</topic><topic>Nickel</topic><topic>regression analysis</topic><topic>semi-parametric single-index model</topic><toplevel>online_resources</toplevel><creatorcontrib>Yang Weng</creatorcontrib><creatorcontrib>Yonghong Zhao</creatorcontrib><creatorcontrib>Guangbo Tang</creatorcontrib><creatorcontrib>Zhengdong Liu</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yang Weng</au><au>Yonghong Zhao</au><au>Guangbo Tang</au><au>Zhengdong Liu</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Prediction of the mechanical properties of hot-rolled C-Mn steels by single index model</atitle><btitle>2013 8th International Conference on Computer Science & Education</btitle><stitle>ICCSE</stitle><date>2013-04</date><risdate>2013</risdate><spage>275</spage><epage>280</epage><pages>275-280</pages><isbn>1467344648</isbn><isbn>9781467344647</isbn><eisbn>1467344621</eisbn><eisbn>9781467344630</eisbn><eisbn>146734463X</eisbn><eisbn>9781467344623</eisbn><abstract>Semi-parametric single index model based approach is proposed for prediction of mechanical properties of hot rolled strip in this paper. Based on industrial production data, a semi-parametric single index model is developed by choosing the appropriate kernel function and window width to predict the yield strength, tensile strength and elongation. When data samples are limited, compared with regression method and neural network method, the prediction results show that the semi-parametric single-index model based method is more adaptive and the prediction performance is superior to both regression and neural network methods.</abstract><pub>IEEE</pub><doi>10.1109/ICCSE.2013.6553924</doi><tpages>6</tpages></addata></record> |
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| subjects | Computers hot strip rolling Indexes Mechanical factors mechanical property prediction neural network Nickel regression analysis semi-parametric single-index model |
| title | Prediction of the mechanical properties of hot-rolled C-Mn steels by single index model |
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