View in EDS

Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.

Saved in:
Bibliographic Details
Title: Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.
Authors: Uddin MG; School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland; Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland. Electronic address: mdgalal.uddin@universityofgalway.ie., Nash S; School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland., Rahman A; School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, Australia; The Gulbali Institute of Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, Australia., Dabrowski T; Marine Institute, Rinville, Ireland., Olbert AI; School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland; Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland.
Source: Environmental research [Environ Res] 2024 Feb 01; Vol. 242, pp. 117755. Date of Electronic Publication: 2023 Nov 25.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0147621 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1096-0953 (Electronic) Linking ISSN: 00139351 NLM ISO Abbreviation: Environ Res Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 38008200
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Uddin+MG%22">Uddin MG</searchLink>; School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland; Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland. Electronic address: mdgalal.uddin@universityofgalway.ie.<br /><searchLink fieldCode="AU" term="%22Nash+S%22">Nash S</searchLink>; School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland.<br /><searchLink fieldCode="AU" term="%22Rahman+A%22">Rahman A</searchLink>; School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, Australia; The Gulbali Institute of Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, Australia.<br /><searchLink fieldCode="AU" term="%22Dabrowski+T%22">Dabrowski T</searchLink>; Marine Institute, Rinville, Ireland.<br /><searchLink fieldCode="AU" term="%22Olbert+AI%22">Olbert AI</searchLink>; School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland; Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%220147621%22">Environmental research</searchLink> [Environ Res] 2024 Feb 01; Vol. 242, pp. 117755. <i>Date of Electronic Publication: </i>2023 Nov 25.
– 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="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>0147621 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1096-0953 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200139351%22">00139351 </searchLink><i>NLM ISO Abbreviation: </i>Environ Res <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=38008200
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.envres.2023.117755
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 117755
    Titles:
      – TitleFull: Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Uddin MG
      – PersonEntity:
          Name:
            NameFull: Nash S
      – PersonEntity:
          Name:
            NameFull: Rahman A
      – PersonEntity:
          Name:
            NameFull: Dabrowski T
      – PersonEntity:
          Name:
            NameFull: Olbert AI
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Text: 2024 Feb 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-electronic
              Value: 1096-0953
          Numbering:
            – Type: volume
              Value: 242
          Titles:
            – TitleFull: Environmental research
              Type: main
ResultId 1