View in EDS HTML Full Text PDF Full Text

Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks.

Saved in:
Bibliographic Details
Title: Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks.
Authors: Nazari, Ali1, alinazari84@aut.ac.ir, Hajiallahyari, Hadi1, Rahimi, Ali1, Khanmohammadi, Hamid1, Amini, Mohammad1
Source: Neural Computing & Applications; Feb2019 Supplement 2, Vol. 31 Issue 2, p733-741, 9p
Database: Applied Science & Technology Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 135840228
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Nazari%2C+Ali%22">Nazari, Ali</searchLink><relatesTo>1</relatesTo>, <i>alinazari84@aut.ac.ir</i><br /><searchLink fieldCode="AU" term="%22Hajiallahyari%2C+Hadi%22">Hajiallahyari, Hadi</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Rahimi%2C+Ali%22">Rahimi, Ali</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Khanmohammadi%2C+Hamid%22">Khanmohammadi, Hamid</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Amini%2C+Mohammad%22">Amini, Mohammad</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Neural+Computing+%26+Applications%22">Neural Computing & Applications</searchLink>; Feb2019 Supplement 2, Vol. 31 Issue 2, p733-741, 9p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=135840228
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00521-012-1082-3
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 733
    Titles:
      – TitleFull: Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Nazari, Ali
      – PersonEntity:
          Name:
            NameFull: Hajiallahyari, Hadi
      – PersonEntity:
          Name:
            NameFull: Rahimi, Ali
      – PersonEntity:
          Name:
            NameFull: Khanmohammadi, Hamid
      – PersonEntity:
          Name:
            NameFull: Amini, Mohammad
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 02
              M: 02
              Text: Feb2019 Supplement 2
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-print
              Value: 09410643
          Numbering:
            – Type: volume
              Value: 31
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Neural Computing & Applications
              Type: main
ResultId 1