comparing geostatistics techniques and nonparametric k-nearest neighbor technique for predicting soil saturated hydraulic conductivity
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a nonparametric model by using k-nearest neighbor technique for predicting soil saturated hydraulic conductivity
abstract saturated hydraulic conductivity (ks) is needed for many studies related to water and solute transport, but often cannot be measured because of practical and/or cost-related reasons. nonparametric approaches are being used in various fields to estimate continuous variables. one type of the nonparametric lazy learning algorithms, a k-nearest neighbor (k-nn) algorithm, was introduced and...
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Nonparametric approaches are being used in various fields to address classification type problems, as well as to estimate continuous variables. One type of the nonparametric lazy learning algorithms, a k-nearest neighbor (k-NN) algorithm has been applied to estimate water retention at 233and 21500-kPa matric potentials. Performance of the algorithm has subsequently been tested against estimatio...
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پژوهش های حفاظت آب و خاکجلد ۲۰، شماره ۵، صفحات ۱۴۷-۱۶۲
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