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.


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    Title :

    MACHINE LEARNING OPTIMIZATION THROUGH RANDOMIZED AUTONOMOUS CROP PLANTING


    Contributors:

    Publication date :

    2023-02-23


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    A01B SOIL WORKING IN AGRICULTURE OR FORESTRY , Bodenbearbeitung in Land- oder Forstwirtschaft / A01C Pflanzen , PLANTING / A01G Gartenbau , HORTICULTURE / A01M Tierfang, Tierfallen oder Abschreckvorrichtungen für Tiere , CATCHING, TRAPPING OR SCARING OF ANIMALS / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen



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