View in EDS

Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network.

Saved in:
Bibliographic Details
Title: Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network.
Authors: Jiang, Jingchao1, Hu, Guobiao1, ghu211@aucklanduni.ac.nz, Li, Xiao2, Xu, Xun1, Zheng, Pai1, Stringer, Jonathan1
Source: Virtual & Physical Prototyping; Sep2019, Vol. 14 Issue 3, p253-266, 14p
Database: Applied Science & Technology Source
FullText Text:
  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 136072592
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Jiang%2C+Jingchao%22">Jiang, Jingchao</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Hu%2C+Guobiao%22">Hu, Guobiao</searchLink><relatesTo>1</relatesTo>, <i>ghu211@aucklanduni.ac.nz</i><br /><searchLink fieldCode="AU" term="%22Li%2C+Xiao%22">Li, Xiao</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Xu%2C+Xun%22">Xu, Xun</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zheng%2C+Pai%22">Zheng, Pai</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Stringer%2C+Jonathan%22">Stringer, Jonathan</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Virtual+%26+Physical+Prototyping%22">Virtual & Physical Prototyping</searchLink>; Sep2019, Vol. 14 Issue 3, p253-266, 14p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=136072592
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/17452759.2019.1576010
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 253
    Titles:
      – TitleFull: Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Jiang, Jingchao
      – PersonEntity:
          Name:
            NameFull: Hu, Guobiao
      – PersonEntity:
          Name:
            NameFull: Li, Xiao
      – PersonEntity:
          Name:
            NameFull: Xu, Xun
      – PersonEntity:
          Name:
            NameFull: Zheng, Pai
      – PersonEntity:
          Name:
            NameFull: Stringer, Jonathan
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Text: Sep2019
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-print
              Value: 17452759
          Numbering:
            – Type: volume
              Value: 14
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Virtual & Physical Prototyping
              Type: main
ResultId 1