Enhanced pedotransfer functions with support vector machines to predict water retention of calcareous soil

By Muhammed Khlosi, Monther Alhamdoosh, A. Douaik, Donald Gabriëls, Wim Cornelis. 2016

56 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Soil Science

View Paper: https://www.semanticscholar.org/paper/5f1c3c710a9f11423fee19616d9de4e2ac53440b

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1. Andrew Margenot
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3. M. S. Demyan
4. L. Deiss
5. Abhinav Sharma

Citations in the corpus

• Tuning support vector machines regression models improves prediction accuracy of soil properties in MIR spectroscopy (2020, methodology): “Grid search has also been used in other soil applications beyond infrared spectroscopy such as prediction of soil pore-water pressure, soil heavy metal concentrations, and soil water retention potential (Mirhosseini, 2017; Babangida et al., 2016; Wu et al., 2016; Khlosi et al., 2016).”