Maschinenlernoptimierung durch Randomisierten Autonomen Pflanzenanbau

Details

Veröffentlichungs-Nr.

EP4136952

Aktenzeichen

EP22185832

Anmeldetag

19. Juli 2022

Veröffentlichung

22. Februar 2023

Rechtsraum

EP

IPC

A01C21/00G06N3/08

Abstract

Systems and methods automate the design and execution of randomized experiments. Portions of a field are planted using an agricultural vehicle configured to randomly vary planting parameters when planting a portion of the field. A resulting crop outcome across each portion or sub-portion of the field is observed. A training set of data is generated that includes the varied planting parameters and the associated crop outcomes for each portion of the field. A machine-learned model is trained using the training set of data and is configured to predict a crop outcome for a portion of the field based on historical and forecast conditions and a set of planting parameters applied to a portion of the field. For subsequent iterations, for a target portion of the field, the machine-learned model can be applied to identify a set of planting parameters for planting the target portion of the field to optimize a desired crop outcome.

Anmelder

Firma

Deere & Company

Land

🇺🇸 USA

Fachgebiete