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Evaluation and Comparison of GRNN, MLP and RBF Neural Networks for Estimating Cucumber, Tomato and Reference Crops’ Evapotranspiration in Greenhouse Condition

Document Type : Research Paper

Author

  • Vahid Rezaverdinejad

Keywords

  • Air vapor pressure
  • Artificial neural network
  • Cucumber
  • evapotranspiration
  • Incoming radiation
  • Tomato

Water and Soil Science
Volume 25, 4/2
March 2016
Pages 123-136

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  • HARVARD
  • CHICAGO
  • VANCOUVER

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  • Article View: 2,174
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APA

Rezaverdinejad, V. (2016). Evaluation and Comparison of GRNN, MLP and RBF Neural Networks for Estimating Cucumber, Tomato and Reference Crops’ Evapotranspiration in Greenhouse Condition. Water and Soil Science, 25(4/2), 123-136.

MLA

Rezaverdinejad, V. . "Evaluation and Comparison of GRNN, MLP and RBF Neural Networks for Estimating Cucumber, Tomato and Reference Crops’ Evapotranspiration in Greenhouse Condition", Water and Soil Science, 25, 4/2, 2016, 123-136.

HARVARD

Rezaverdinejad, V. (2016). 'Evaluation and Comparison of GRNN, MLP and RBF Neural Networks for Estimating Cucumber, Tomato and Reference Crops’ Evapotranspiration in Greenhouse Condition', Water and Soil Science, 25(4/2), pp. 123-136.

CHICAGO

V. Rezaverdinejad, "Evaluation and Comparison of GRNN, MLP and RBF Neural Networks for Estimating Cucumber, Tomato and Reference Crops’ Evapotranspiration in Greenhouse Condition," Water and Soil Science, 25 4/2 (2016): 123-136,

VANCOUVER

Rezaverdinejad, V. Evaluation and Comparison of GRNN, MLP and RBF Neural Networks for Estimating Cucumber, Tomato and Reference Crops’ Evapotranspiration in Greenhouse Condition. Water and Soil Science, 2016; 25(4/2): 123-136.

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