Prediction of consistency parameters of fen soils by neural networks
TL;DRAbstract
This paper presents application of artificial neural networks (ANNs) for prediction of consistency parameters (plastic limit, liquid limit) of fen soils in comparison with the standard regression analysis. All samples of cohesive soils were retrieved from the Wisłok river floodplain, in the vicinity of Rzeszów, near Lisia Góra (Fox Mountain) reserve. Basic fractions (clay, silt, sand) of fen soils are independent variables in modeling of soil properties. Two regression models and a standard multi-layer back-propagation net have been used.
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This paper presents application of artificial neural networks (ANNs) for prediction of consistency parameters (plastic limit, liquid limit) of fen soils in comparison with the standard regression analysis. All samples of cohesive soils were retrieved from the Wisłok river floodplain, in the vicinity of Rzeszów, near Lisia Góra (Fox Mountain) reserve. Basic fractions (clay, silt, sand) of fen soils are independent variables in modeling of soil properties. Two regression models and a standard multi-layer back-propagation net have been used.
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