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Predicting the Dielectric Constant–Water Content Relationship Using Artificial Neural Networks

^a Department of Water Resources Engineering, Lund University, Box 118, SE-221 00 Lund, Sweden
^b Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
^c Department of Crop Physiology and Soil Science P.O. Box 50 DK-8830 Tjele, Denmark

View larger version (20K): [in a new window]   Fig. 1. Schematic description of a 2-4-2 ANN.

View larger version (14K): [in a new window]   Fig. 2. Root mean square error using standardized data for different number of hidden nodes, k.