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Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering.

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Title: Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering.
Authors: Diaz-Rozo, Javier1,2, jdiaz@ainguraiiot.com, Bielza, Concha2, Larrañaga, Pedro2
Source: Engineering Applications of Artificial Intelligence; Mar2020, Vol. 89, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 141609625
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering.
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.engappai.2019.103434
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Titles:
      – TitleFull: Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering.
        Type: main
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            NameFull: Diaz-Rozo, Javier
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            NameFull: Bielza, Concha
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            NameFull: Larrañaga, Pedro
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          Dates:
            – D: 01
              M: 03
              Text: Mar2020
              Type: published
              Y: 2020
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              Value: 89
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            – TitleFull: Engineering Applications of Artificial Intelligence
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