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Refinado por: autor: Demattê, J remover autor: Stenberg, B remover
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Improving the prediction performance of a large tropical vis-NIR spectroscopic soil library from Brazil by clustering into smaller subsets or use of data mining calibration techniques
Improving the prediction performance of a large tropical vis-NIR spectroscopic soil library from Brazil by clustering into smaller subsets or use of data mining calibration techniques
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Improving the prediction performance of a large tropical vis-NIR spectroscopic soil library from Brazil by clustering into smaller subsets or use of data mining calibration techniques

Suzana Romeiro Araújo J Wetterlind; José Alexandre Melo Demattê; B Stenberg

European Journal of Soil Science Oxford v. 65, p. 718–729, 2014

Oxford 2014

Item não circula. Consulte sua biblioteca.(Acessar)

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Deste Autor:

  1. Araújo, S
  2. Wetterlind, J
  3. Stenberg, B
  4. Demattê, J

Neste Assunto:

  1. Argilas
  2. Espectroscopia Infravermelha
  3. Matéria Orgânica Do Solo
  4. Mineração De Dados
  5. Solos

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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