Evaluation of machine learning algorithms in the prediction of hydraulic conductivity and soil moisture at the Brazilian Savannah

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Related collections

Most cited references 50

Record: found
Abstract: not found
Article: not found

Random Forests

Leo Breiman (2001)

0 comments Cited 9337 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

rosetta: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions

Marcel Schaap, Feike Leij, Martinus Th. van Genuchten (2001)

0 comments Cited 304 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

A new model for predicting the hydraulic conductivity of unsaturated porous media

Yechezkel Mualem (1976)

0 comments Cited 275 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Title: Geoderma Regional

Abbreviated Title: Geoderma Regional

Publisher: Elsevier BV

ISSN (Print): 23520094

Publication date Created: September 2022

Publication date (Print): September 2022

Volume: 30

Page: e00569

Article

DOI: 10.1016/j.geodrs.2022.e00569

SO-VID: 0646ccf2-61da-4018-ae52-e25734ea931d

License:

https://www.elsevier.com/tdm/userlicense/1.0/

History

Data availability:

Comments

Comment on this article

scite_

Smart Citations

Citing PublicationsSupportingMentioningContrasting

View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.