汽车排放预测模型中数据挖掘技术的应用

The Application of Data Mining Technology in Vehicle Emission Prediction Models

在重型柴油机国六法规中,整车厂商不仅要符合汽车排放达标,而且要将汽车运行数据进行上传。可见,汽车的排放的重要性被强化,无论是国家监控平台,或者整车厂家,也纷纷投入汽车排放预测模型的功能开发中。本文针对汽车氮氧化物(NOx排放)排放预测模型中,所应用到的数据挖掘技术,如有监督学习、聚类分析、回归分析等技术,在模型中的应用进行举例说明,帮助数据分析者们有效利用数据挖掘技术,精准定位应用类型,帮助我们更好的搭建预测模型。

In the National VI regulations for heavy-duty diesel engines, vehicle manufacturers must not only meet the vehicle emission standards, but also upload the vehicle operation data. It can be seen that the importance of automobile emissions has been strengthened, whether it is the national monitoring platform or vehicle manufacturers, they have also invested in the functional development of vehicle emission prediction models. This paper provides an example of the application of data mining techniques, such as supervised learning, cluster analysis, regression analysis and other technologies, in the model to help data analysts effectively use data mining technology, accurately locate the application type, and help us better build a prediction model.