Prognostic Models of Panicum virgatum L. Using Artificial Neural Networks
The article shows the possibility of using modern methods of artificial intelligence to calculate the yield of biomass of crops according to the given set input data (fertilizer doses, agrochemical parameters of the soil, productivity). The study reflects the results of testing a model of a compute...
Guardado en:
Autores principales: | Vasyl Ivanovych Lopushniak, Halyna Myhaylovna Hrytsuliak, Anatoliy Viktorovych Bykin, Nadia Petryvna Bordyuzha, Larysa Oleksandryvna Semenko, Myroslava Stepanivna Polutrenko, Yulia Zinoviyivna Kotsyubynska |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Polish Society of Ecological Engineering (PTIE)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/09a53f710fc643749422b8b4b8edcebb |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Enhancement of switchgrass (Panicum virgatum l.) early growth as affected by composts
por: Traversa,A, et al.
Publicado: (2014) -
SNP discovery with EST and NextGen sequencing in switchgrass (Panicum virgatum L.).
por: Elhan S Ersoz, et al.
Publicado: (2012) -
Comparative Study on Quality of Fuel Pellets from Switchgrass Treated with Different White-Rot Fungi
por: Onu Onu Olughu, et al.
Publicado: (2021) -
The road to conscious machines: AI through failed ideas
por: Roman Krzanowski
Publicado: (2021) - Ai communications the European journal on artificial intelligence.