机器学习算法与3σ定律在智慧温室数据预处理中的应用

Application of Machine Learning Algorithms and 3σ Law in Data Preprocessing of Smart Greenhouse

为了有效解决在极端环境下智慧温室内部分传感器不工作导致产生缺失值及数据准确性的问题。以智慧温室传感器采集的数据为研究对象,利用多种机器学习算法进行数据插补,同时利用3σ定律和数据融合对插补后的数据集进行预处理,提高了数据集的完整性与准确性。为技术人员进一步分析、处理数据,实现智慧温室精确控制提供了更加准确可靠的数据源。

In order to effectively solve the problems of missing values and data accuracy caused by some sensors not working in the smart greenhouse in the extreme environment.The paper takes the data collected by the smart greenhouse sensor as the research object, and a variety of machine learning algorithms are used for data interpolation, and 3σ law and data fusion are used to preprocess the interpolated data set, which improves the integrity and accuracy of the data set. The study will provide a more accurate and reliable data source for technicians to further analyze and process data, and to realize the precise control of smart greenhouse.