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Open AccessArticle10.24423/cames.56

Prediction of consistency parameters of fen soils by neural networks

Artur Borowiec,Krzysztof Wilk-2020-10-08-SHILAP Revista de lepidopterología
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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.

Keywords

Soil waterSiltArtificial neural networkAtterberg limitsConsistency (knowledge bases)Soil scienceEnvironmental scienceFloodplain

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