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Prediction of mechanical properties of rail pads under in-service conditions through machine learning algorithms.

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Title: Prediction of mechanical properties of rail pads under in-service conditions through machine learning algorithms.
Authors: Ferreño, Diego1, Sainz-Aja, Jose A.1, sainzajaj@unican.es, Carrascal, Isidro A.1, Cuartas, Miguel2, Pombo, Joao3,4, Casado, Jose A.1, Diego, Soraya1
Source: Advances in Engineering Software (1992); Jan2021, Vol. 151, 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: 147183118
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Prediction of mechanical properties of rail pads under in-service conditions through machine learning algorithms.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=147183118
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.advengsoft.2020.102927
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      – Code: eng
        Text: English
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      – TitleFull: Prediction of mechanical properties of rail pads under in-service conditions through machine learning algorithms.
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            NameFull: Ferreño, Diego
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            NameFull: Sainz-Aja, Jose A.
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            NameFull: Cuartas, Miguel
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            NameFull: Pombo, Joao
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            NameFull: Casado, Jose A.
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            – D: 01
              M: 01
              Text: Jan2021
              Type: published
              Y: 2021
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              Value: 151
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            – TitleFull: Advances in Engineering Software (1992)
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