View in EDS

Evaluation of the proposed algorithm across varying agent counts (1,000, 3,000, and 5,000), using four metrics: Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), Silhouette Score, and Davies-Bouldin Index.

Saved in:
Bibliographic Details
Title: Evaluation of the proposed algorithm across varying agent counts (1,000, 3,000, and 5,000), using four metrics: Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), Silhouette Score, and Davies-Bouldin Index.
Authors: Victoria Erofeeva, Oleg Granichin, Vikentii Pankov, Zeev Volkovich
Publication Year: 2025
Subject Terms: Cell Biology, Infectious Diseases, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, world datasets show, unlike traditional methods, trained neural network, dynamic network changes, system &# 8217, minimal communication overhead, efficient decentralized clustering, system adapts, clustering structure, clustering accuracy, %22">xlink ">, static topologies, paper presents, iot ), immediate results, highly suitable, generate compact, fly processing, dynamical multi, distributed environments, distributed aggregation, dimensionality reduction, data must, consistent summaries, consensus protocol
Description: Each metric is plotted against the number of agents. The proposed method demonstrates consistently superior performance compared to the baseline distributed approach. A slight degradation in clustering quality at 5,000 agents indicates potential scalability limitations, which may be addressed through architectural modifications such as increased network depth or additional internal channels.
Document Type: still image
Language: unknown
DOI: 10.1371/journal.pone.0327396.g003
Availability: https://doi.org/10.1371/journal.pone.0327396.g003
https://figshare.com/articles/figure/Evaluation_of_the_proposed_algorithm_across_varying_agent_counts_1_000_3_000_and_5_000_using_four_metrics_Adjusted_Rand_Index_ARI_Normalized_Mutual_Information_NMI_Silhouette_Score_and_Davies-Bouldin_Index_/29667957
Rights: CC BY 4.0
Accession Number: edsbas.7E4862F1
Database: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://doi.org/10.1371/journal.pone.0327396.g003#
    Name: EDS - BASE (s4221598)
    Category: fullText
    Text: View record from BASE
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Erofeeva%20V
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsbas
DbLabel: BASE
An: edsbas.7E4862F1
RelevancyScore: 931
AccessLevel: 3
PubType: Image
PubTypeId: image
PreciseRelevancyScore: 931.3056640625
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Evaluation of the proposed algorithm across varying agent counts (1,000, 3,000, and 5,000), using four metrics: Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), Silhouette Score, and Davies-Bouldin Index.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Victoria+Erofeeva%22">Victoria Erofeeva</searchLink><br /><searchLink fieldCode="AR" term="%22Oleg+Granichin%22">Oleg Granichin</searchLink><br /><searchLink fieldCode="AR" term="%22Vikentii+Pankov%22">Vikentii Pankov</searchLink><br /><searchLink fieldCode="AR" term="%22Zeev+Volkovich%22">Zeev Volkovich</searchLink>
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2025
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Cell+Biology%22">Cell Biology</searchLink><br /><searchLink fieldCode="DE" term="%22Infectious+Diseases%22">Infectious Diseases</searchLink><br /><searchLink fieldCode="DE" term="%22Biological+Sciences+not+elsewhere+classified%22">Biological Sciences not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+Sciences+not+elsewhere+classified%22">Mathematical Sciences not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Systems+not+elsewhere+classified%22">Information Systems not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22world+datasets+show%22">world datasets show</searchLink><br /><searchLink fieldCode="DE" term="%22unlike+traditional+methods%22">unlike traditional methods</searchLink><br /><searchLink fieldCode="DE" term="%22trained+neural+network%22">trained neural network</searchLink><br /><searchLink fieldCode="DE" term="%22dynamic+network+changes%22">dynamic network changes</searchLink><br /><searchLink fieldCode="DE" term="%22system+%26#+8217%22">system &# 8217</searchLink><br /><searchLink fieldCode="DE" term="%22minimal+communication+overhead%22">minimal communication overhead</searchLink><br /><searchLink fieldCode="DE" term="%22efficient+decentralized+clustering%22">efficient decentralized clustering</searchLink><br /><searchLink fieldCode="DE" term="%22system+adapts%22">system adapts</searchLink><br /><searchLink fieldCode="DE" term="%22clustering+structure%22">clustering structure</searchLink><br /><searchLink fieldCode="DE" term="%22clustering+accuracy%22">clustering accuracy</searchLink><br /><searchLink fieldCode="DE" term="%22xlink+">%22">xlink "></searchLink><br /><searchLink fieldCode="DE" term="%22static+topologies%22">static topologies</searchLink><br /><searchLink fieldCode="DE" term="%22paper+presents%22">paper presents</searchLink><br /><searchLink fieldCode="DE" term="%22iot+%29%22">iot )</searchLink><br /><searchLink fieldCode="DE" term="%22immediate+results%22">immediate results</searchLink><br /><searchLink fieldCode="DE" term="%22highly+suitable%22">highly suitable</searchLink><br /><searchLink fieldCode="DE" term="%22generate+compact%22">generate compact</searchLink><br /><searchLink fieldCode="DE" term="%22fly+processing%22">fly processing</searchLink><br /><searchLink fieldCode="DE" term="%22dynamical+multi%22">dynamical multi</searchLink><br /><searchLink fieldCode="DE" term="%22distributed+environments%22">distributed environments</searchLink><br /><searchLink fieldCode="DE" term="%22distributed+aggregation%22">distributed aggregation</searchLink><br /><searchLink fieldCode="DE" term="%22dimensionality+reduction%22">dimensionality reduction</searchLink><br /><searchLink fieldCode="DE" term="%22data+must%22">data must</searchLink><br /><searchLink fieldCode="DE" term="%22consistent+summaries%22">consistent summaries</searchLink><br /><searchLink fieldCode="DE" term="%22consensus+protocol%22">consensus protocol</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Each metric is plotted against the number of agents. The proposed method demonstrates consistently superior performance compared to the baseline distributed approach. A slight degradation in clustering quality at 5,000 agents indicates potential scalability limitations, which may be addressed through architectural modifications such as increased network depth or additional internal channels.
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: still image
– Name: Language
  Label: Language
  Group: Lang
  Data: unknown
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1371/journal.pone.0327396.g003
– Name: URL
  Label: Availability
  Group: URL
  Data: https://doi.org/10.1371/journal.pone.0327396.g003<br />https://figshare.com/articles/figure/Evaluation_of_the_proposed_algorithm_across_varying_agent_counts_1_000_3_000_and_5_000_using_four_metrics_Adjusted_Rand_Index_ARI_Normalized_Mutual_Information_NMI_Silhouette_Score_and_Davies-Bouldin_Index_/29667957
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: CC BY 4.0
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.7E4862F1
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.7E4862F1
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1371/journal.pone.0327396.g003
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Cell Biology
        Type: general
      – SubjectFull: Infectious Diseases
        Type: general
      – SubjectFull: Biological Sciences not elsewhere classified
        Type: general
      – SubjectFull: Mathematical Sciences not elsewhere classified
        Type: general
      – SubjectFull: Information Systems not elsewhere classified
        Type: general
      – SubjectFull: world datasets show
        Type: general
      – SubjectFull: unlike traditional methods
        Type: general
      – SubjectFull: trained neural network
        Type: general
      – SubjectFull: dynamic network changes
        Type: general
      – SubjectFull: system &# 8217
        Type: general
      – SubjectFull: minimal communication overhead
        Type: general
      – SubjectFull: efficient decentralized clustering
        Type: general
      – SubjectFull: system adapts
        Type: general
      – SubjectFull: clustering structure
        Type: general
      – SubjectFull: clustering accuracy
        Type: general
      – SubjectFull: xlink ">
        Type: general
      – SubjectFull: static topologies
        Type: general
      – SubjectFull: paper presents
        Type: general
      – SubjectFull: iot )
        Type: general
      – SubjectFull: immediate results
        Type: general
      – SubjectFull: highly suitable
        Type: general
      – SubjectFull: generate compact
        Type: general
      – SubjectFull: fly processing
        Type: general
      – SubjectFull: dynamical multi
        Type: general
      – SubjectFull: distributed environments
        Type: general
      – SubjectFull: distributed aggregation
        Type: general
      – SubjectFull: dimensionality reduction
        Type: general
      – SubjectFull: data must
        Type: general
      – SubjectFull: consistent summaries
        Type: general
      – SubjectFull: consensus protocol
        Type: general
    Titles:
      – TitleFull: Evaluation of the proposed algorithm across varying agent counts (1,000, 3,000, and 5,000), using four metrics: Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), Silhouette Score, and Davies-Bouldin Index.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Victoria Erofeeva
      – PersonEntity:
          Name:
            NameFull: Oleg Granichin
      – PersonEntity:
          Name:
            NameFull: Vikentii Pankov
      – PersonEntity:
          Name:
            NameFull: Zeev Volkovich
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
ResultId 1