Comparison of Different Machine Learning Methods for Predicting Cation Exchange Capacity Using Environmental and Remote Sensing Data

This study was conducted to examine the capability of topographic features and remote sensing data in combination with other auxiliary environmental variables (geology and geomorphology) to predict CEC by using different machine learning models ((random forest (RF), k-nearest neighbors (kNNs), Cubis...

Descripción completa

Detalles Bibliográficos
Autores principales: Saidi, Sanaz, Ayoubi, Shamsollah, Shirvani, Mehran, Azizi, Kamran, Zeraatpisheh, Mojtaba
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506071/
https://www.ncbi.nlm.nih.gov/pubmed/36146239
http://dx.doi.org/10.3390/s22186890

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506071/
https://www.ncbi.nlm.nih.gov/pubmed/36146239
http://dx.doi.org/10.3390/s22186890

Ejemplares similares