Papers: 10.1038/s41598-020-72018-2
https://doi.org/10.1038/s41598-020-72018-2
Spatial structure, parameter nonlinearity, and intelligent algorithms in constructing pedotransfer functions from large-scale soil legacy data
Cited by: 6
Author(s): Poulamee Chakraborty, Bhabani S. Das, Hitesh B. Vasava, Niranjan Panigrahi, Priyabrata Santra
Published: almost 5 years ago
Software Mentions 9
cran: glmnet
Lasso and Elastic-Net Regularized Generalized Linear ModelsPapers that mentioned: 1,607
Very Likely Science (100)
cran: gstat
Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and SimulationPapers that mentioned: 138
Very Likely Science (100)
Very Likely Science (85)
cran: randomForest
Breiman and Cutler's Random Forests for Classification and RegressionPapers that mentioned: 1,447
Very Likely Science (100)
Very Likely Science (100)
pypi: environment
This library provides parsing and validation of environment variables.Papers that mentioned: 569
Very Likely Science (65)
Very Likely Science (100)
pypi: lattice
A framework for developing data models, including schema development and documentation.Papers that mentioned: 251
Very Likely Science (80)
Very Likely Science (90)