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  • Spatially distributed modeling of soil organic matter across China : An application of artificial neural network approach
  • Analyse en composantes principales ; Chine ; Distribution spatiale ; Krigeage ; Matière organique ; Modèle ; Propriétés du sol ; Réseau neuronal ; Sol
  • China ; Krigeage ; Model ; Neural network ; Organic materials ; Principal components analysis ; Soil ; Soil properties ; Spatial distribution
  • Análisis en componentes principales ; China ; Distribución espacial ; Krigeage ; Materia orgánica ; Modelo ; Propiedades del suelo ; Red neural ; Suelo
  • This study proposed a radial basis function neural networks model (RBFNN), combined with principal component analysis (PCA), to predict the spatial distribution of soil organic matter (SOM) content across China. To assess its feasibility, 6 241 soil
  • 2013
  • A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), generalized linear model (GLM), and multiple linear regression (MLR) models are appropriate
  • 2013
  • , Geographic Information System, and Neural Network) as a tool to compare and contrasts the advantages and limitations of two landslides susceptibility models : Stability Index MAPping (SINMAP) and Multiple Logistic Regression (MLR). Both models are embedded
  • 2013