论文标题
从数据中学习以优化精确农业的控制
Learning from Data to Optimize Control in Precision Farming
论文作者
论文摘要
精密耕作是许多人到2050年到2050年全球农产品对全球农产品的需求增加70％的方法，这是一种减少的需求和有效利用水资源的需求。精确耕作的出现的催化剂是卫星定位和导航，其次是卫星互联网，生成了大量信息，可用于实时优化耕作过程。数据挖掘，预测性建模和机器学习分析模式中的统计工具在历史数据中进行了预测，以预测未来事件以及智能行动。本期特刊介绍了统计推断，机器学习和精确农业最佳控制方面的最新发展。
Precision farming is one way of many to meet a 70 percent increase in global demand for agricultural products on current agricultural land by 2050 at reduced need of fertilizers and efficient use of water resources. The catalyst for the emergence of precision farming has been satellite positioning and navigation followed by Internet-of-Things, generating vast information that can be used to optimize farming processes in real-time. Statistical tools from data mining, predictive modeling, and machine learning analyze pattern in historical data, to make predictions about future events as well as intelligent actions. This special issue presents the latest development in statistical inference, machine learning and optimum control for precision farming.
