几种支持向量机模型对大气污染物PM10的预测

S. Sunori, P. Negi, Kapil Ghai, Amit Mittal, M. Lohani, M. Manu, P. Juneja
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引用次数: 1

摘要

空气污染主要由3种有害污染物造成,即SO2、NO2和PM(颗粒物)。在颗粒物质内部,固体颗粒与液滴混合在一起。PM有两种类型,即PM10和PM2.5。PM10颗粒直径小于等于10毫米,PM2.5颗粒直径小于等于2.5毫米。这些微粒会对人类造成非常有害的后果。PM颗粒是由SO2和NO2发生化学反应形成的。因此,了解SO2和NO2的浓度可以作为预测PM的基础。本文利用MATLAB (R2021a)中具有不同核函数的SVM(支持向量机)技术,对给定SO2和NO2污染物浓度下的PM10组分进行了预测。对各预测模型的预测性能进行了评价和比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Air Pollutant PM10 using Various SVM Models
The air pollution is majorly caused by 3 harmful pollutants viz. SO2, NO2 and PM (Particulate Matter). Inside particulate matter, the solid particles are present mixed up with liquid droplets. The PM is of two types viz. PM10 and PM2.5. The diameter of PM10 particles is 10 mm or less, and that of PM2.5 particles is 2.5 mm or less. These particles can cause very harmful consequences on mankind. The PM particles are formed as a result of chemical reaction taking place between SO2 and NO2. So, the knowledge of SO2 and NO2 concentrations can be a base for the prediction of PM. In this article, an effort has been put to predict PM10 component for given SO2 and NO2 pollutant concentrations using SVM (Support Vector Machine) techniques with different kernel functions in MATLAB (R2021a). The prediction performance of all prediction models is evaluated and compared.
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