论文标题
通过动态线性模型进行天气监测的质量控制
Quality Control in Weather Monitoring with Dynamic Linear Models
论文作者
论文摘要
农业的决定经常基于天气。随着现成的天气站的可用性和负担能力的增加，农民能够获取本地天气信息。但是，由于传感器和安装质量的不确定性，农民有可能基于错误的数据做出不良决策的风险。我们提出了一种自动化方法，以对天气传感器进行质量控制。我们的方法使用时间序列建模和数据融合与贝叶斯原理，以提供不确定性量化的预测。这些预测和不确定性用于估计传感器观察的有效性。我们测试温度，风能和湿度数据，并使误差率高于80％和低于11％的假负率。
Decisions in agriculture are frequently based on weather. With an increase in the availability and affordability of off-the-shelf weather stations, farmers able to acquire localised weather information. However, with uncertainty in the sensor and installation quality, farmers are at risk of making poor decisions based on incorrect data. We present an automated approach to perform quality control on weather sensors. Our approach uses time-series modelling and data fusion with Bayesian principles to provide predictions with uncertainty quantification. These predictions and uncertainty are used to estimate the validity of a sensor observation. We test on temperature, wind, and humidity data and achieve error hit rates above 80% and false negative rates below 11%.
