首页> 外国专利> USING MACHINE LEARNING-BASED SEED HARVEST MOISTURE PREDICTIONS TO IMPROVE A COMPUTER-ASSISTED AGRICULTURAL FARM OPERATION

USING MACHINE LEARNING-BASED SEED HARVEST MOISTURE PREDICTIONS TO IMPROVE A COMPUTER-ASSISTED AGRICULTURAL FARM OPERATION

机译:使用基于机器学习的种子收获水份预测来改善计算机辅助的农业农场经营

摘要

Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.
机译:实施例生成用于农业领域的数字计划。在一个实施例中,模型接收数字输入,该数字输入包括压力风险数据,产品成熟度数据,田间位置数据,种植日期数据和/或收获日期数据。该模型将数字输入集与与压力风险数据相关的阈值数据进行数学关联。该模型用于为一组产品成熟度和现场位置组合生成压力风险预测数据。在数字计划中,可以基于压力风险预测数据来调整产品成熟度数据或种植日期数据或收获日期数据或田间位置数据。数字计划可以被发送到现场管理器计算设备。可以响应于数字计划来移动农业设备。

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