Comparison of artificial neural network and regression pedotransfer functions for prediction of soil water retention and saturated hydraulic conductivity

Soil and Tillage Research

Volumn 90, Issue 1-2, 2006, Pages 108-116

  Merdun, Hasan ^a   Çinar, Özer ^a   Meral, Ramazan ^a   Apan, Mehmet ^b  

^a KAHRAMANMARAS SUTCU IMAM UNIVERSITY   (Turkey)

^b ONDOKUZ MAYIS UNIVERSITY   (Turkey)

Author keywords

Artificial neural network; Hydraulic parameters; Pedotransfer function; Prediction; Regression; Soil properties

Indexed keywords

ALGORITHMS; FLOW OF WATER; HYDROLOGY; NEURAL NETWORKS; PARTICLE SIZE ANALYSIS; REGRESSION ANALYSIS;

HYDRAULIC PARAMETERS; PEDOTRANSFER FUNCTION; PREDICTION; REGRESSION; SOIL PROPERTIES;

SOIL CONSERVATION;

ARTIFICIAL NEURAL NETWORK; HYDRAULIC CONDUCTIVITY; PEDOTRANSFER FUNCTION; REGRESSION ANALYSIS; SOIL PROPERTY; SOIL WATER; WATER RETENTION;

EID: 33746893825     PISSN: 01671987     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.still.2005.08.011     Document Type: Article

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