Selection of a suitable model for the prediction of soil water content in north of Iran

Selection of a suitable model for the prediction of soil water content in north of Iran

Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Rosetta model were employed to develop pedotransfers functions (PTFs) for soil moisture prediction using available soil properties for northern soils of Iran. The Rosetta model is based on ANN works in a hierarchical approach to p...

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Bibliographic Details
Main Authors: Leila Esmaeelnejad, Hassan Ramezanpour, Javad Seyedmohammadi, Mahmood Shabanpour
Format: Article
Language:English
Published: Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria 2015-03-01
Series:Spanish Journal of Agricultural Research
Subjects:
multiple linear regression
neural networks
pedotransfer function
Rosetta
soil moisture curve
Online Access:http://revistas.inia.es/index.php/sjar/article/view/6111/2242

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