Comparing machine learning algorithms for predicting and digitally mapping surface soil available phosphorous: a case study from southwestern Iran
Author:
Funder
Iran National Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences
Link
https://link.springer.com/content/pdf/10.1007/s11119-023-10099-5.pdf
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4. Beucher, A., Siemssen, R., Frojo, S., Osterholm, P., Martinkauppi, A., & Eden, P. (2015). Artificial neural network for mapping and characterization of acid sulfate soils: Application to the Sirppujoki River catchment, southwestern Finland. Geoderma, 247–248, 38–50.
5. Biau, G., & Scornet, E. (2016). A random forest-guided tour. TEST, 25, 197–227.
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