Artificial Neural Network System for Predicting Cutting Forces in Helical-End Milling of LaserDeposited Metal Materials.
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| Title: | Artificial Neural Network System for Predicting Cutting Forces in Helical-End Milling of LaserDeposited Metal Materials. |
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| Authors: | Župerl, Uroš1, uros.zuperl@um.si, Kovačič, Miha2, miha.kovacic@store-steel.si |
| Source: | Technical Journal / Tehnički Glasnik; Jun2023, Vol. 17 Issue 2, p223-230, 8p |
| Database: | Applied Science & Technology Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 163751119 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Artificial Neural Network System for Predicting Cutting Forces in Helical-End Milling of LaserDeposited Metal Materials. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Župerl%2C+Uroš%22">Župerl, Uroš</searchLink><relatesTo>1</relatesTo>, <i>uros.zuperl@um.si</i><br /><searchLink fieldCode="AU" term="%22Kovačič%2C+Miha%22">Kovačič, Miha</searchLink><relatesTo>2</relatesTo>, <i>miha.kovacic@store-steel.si</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Technical+Journal+%2F+Tehnički+Glasnik%22">Technical Journal / Tehnički Glasnik</searchLink>; Jun2023, Vol. 17 Issue 2, p223-230, 8p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=163751119 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.31803/tg-20230417145110 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 223 Titles: – TitleFull: Artificial Neural Network System for Predicting Cutting Forces in Helical-End Milling of LaserDeposited Metal Materials. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Župerl, Uroš – PersonEntity: Name: NameFull: Kovačič, Miha IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 18466168 Numbering: – Type: volume Value: 17 – Type: issue Value: 2 Titles: – TitleFull: Technical Journal / Tehnički Glasnik Type: main |
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