Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile

Publikationsart: Zeitschriftenbeiträge (peer-reviewed)
Titel: Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile
Medien: Frontiers in Environmental Science
DOI: 10.3389/fenvs.2021.692959
Band: 9
Artikelnummer: 692959
ISBN: 2296-665X
Autoren: Prof. Dr. Mareike Ließ , Anika Gebauer, Axel Don
Herausgeber: Frontiers
Veröffentlichungsdatum: 25.06.2021
Zitation: Ließ, Mareike; Gebauer, Anika; Don, Axel (2021): Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile. Frontiers in Environmental Science 9, 692959. DOI: 10.3389/fenvs.2021.692959