Prediction of tensile strength in aluminum spot welding using machine learning.
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| Title: | Prediction of tensile strength in aluminum spot welding using machine learning. |
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| Authors: | Seo BW; Applied Laser Technology Group, SAMSUNG SDI Co., Ltd., 150-20, Gongse-ro, Giheung-gu, Yongin-si, 17084, Gyeonggi-do, Republic of Korea., Son HJ; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea., Han SB; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea., Jo IS; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea., Kim CJ; Digital Manufacturing Innovation Division, Research Institute of Medium & Small Shipbuilding, 38-6, Noksansandan 232-ro, Gangseo-gu, Busan, Republic of Korea., Cho YT; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea. ytcho@changwon.ac.kr. |
| Source: | Scientific reports [Sci Rep] 2025 Nov 28; Vol. 15 (1), pp. 42735. Date of Electronic Publication: 2025 Nov 28. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41315525 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Prediction of tensile strength in aluminum spot welding using machine learning. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Seo+BW%22">Seo BW</searchLink>; Applied Laser Technology Group, SAMSUNG SDI Co., Ltd., 150-20, Gongse-ro, Giheung-gu, Yongin-si, 17084, Gyeonggi-do, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Son+HJ%22">Son HJ</searchLink>; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Han+SB%22">Han SB</searchLink>; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Jo+IS%22">Jo IS</searchLink>; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+CJ%22">Kim CJ</searchLink>; Digital Manufacturing Innovation Division, Research Institute of Medium & Small Shipbuilding, 38-6, Noksansandan 232-ro, Gangseo-gu, Busan, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Cho+YT%22">Cho YT</searchLink>; Department of Smart Manufacturing Engineering, Changwon National University, Changwon, 51140, Republic of Korea. ytcho@changwon.ac.kr. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2025 Nov 28; Vol. 15 (1), pp. 42735. <i>Date of Electronic Publication: </i>2025 Nov 28. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101563288 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2045-2322 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220452322%22">20452322 </searchLink><i>NLM ISO Abbreviation: </i>Sci Rep <i>Subsets: </i>MEDLINE; PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41315525 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41598-025-26749-9 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 42735 Titles: – TitleFull: Prediction of tensile strength in aluminum spot welding using machine learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Seo BW – PersonEntity: Name: NameFull: Son HJ – PersonEntity: Name: NameFull: Han SB – PersonEntity: Name: NameFull: Jo IS – PersonEntity: Name: NameFull: Kim CJ – PersonEntity: Name: NameFull: Cho YT IsPartOfRelationships: – BibEntity: Dates: – D: 28 M: 11 Text: 2025 Nov 28 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 2045-2322 Numbering: – Type: volume Value: 15 – Type: issue Value: 1 Titles: – TitleFull: Scientific reports Type: main |
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