Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation

  title={Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation},
  author={Krzysztof Lamorski and Cezary Sławiński and Felix Moreno and Gy{\"o}ngyi Barna and Wojciech Skierucha and Jos{\'e} Luis Arr{\'u}e},
This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention… CONTINUE READING

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