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  • Source: Applied Artificial Intelligence. Unidade: FCFRP

    Subjects: CIÊNCIAS JURÍDICAS, SOLO AGRÍCOLA, CLUSTERS, MINERAÇÃO DE DADOS, DATILOSCOPIA

    Acesso à fonteDOIHow to cite
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    • ABNT

      MAIONE, Camila et al. A cluster analysis methodology for the categorization of soil samples for forensic sciences based on elemental fingerprint. Applied Artificial Intelligence, v. 36, n. 1, p. 1-20, 2022Tradução . . Disponível em: https://doi.org/10.1080/08839514.2021.2010941. Acesso em: 04 nov. 2024.
    • APA

      Maione, C., Costa, N. L. da, Barbosa Júnior, F., & Barbosa, R. M. (2022). A cluster analysis methodology for the categorization of soil samples for forensic sciences based on elemental fingerprint. Applied Artificial Intelligence, 36( 1), 1-20. doi:10.1080/08839514.2021.2010941
    • NLM

      Maione C, Costa NL da, Barbosa Júnior F, Barbosa RM. A cluster analysis methodology for the categorization of soil samples for forensic sciences based on elemental fingerprint [Internet]. Applied Artificial Intelligence. 2022 ; 36( 1): 1-20.[citado 2024 nov. 04 ] Available from: https://doi.org/10.1080/08839514.2021.2010941
    • Vancouver

      Maione C, Costa NL da, Barbosa Júnior F, Barbosa RM. A cluster analysis methodology for the categorization of soil samples for forensic sciences based on elemental fingerprint [Internet]. Applied Artificial Intelligence. 2022 ; 36( 1): 1-20.[citado 2024 nov. 04 ] Available from: https://doi.org/10.1080/08839514.2021.2010941

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