期刊名称：International Journal of Computer Science and Network
印刷版ISSN：2277-5420
出版年度：2018
卷号：7
期号：1
页码：36-39
出版社：IJCSN publisher
摘要：Air pollution is of much concern for the society. There are advancements in the technology leading to developed life. On the
other hand it is responsible for green house gas emissions. There are different sources of GHGs like industries, agriculture construction
sites, etc. GHGs are Nitrous Oxides, Sulphur Dioxide, Carbon Oxides, Methane, CFC and O3. These green house gases are the
pollutants which hampers the quality of air. GHGs are responsible for global warming due to which there is ozone layer depletion. These
pollutants may cause various health problems. Air quality can be assessed based on the Air quality levels (AQL). Air quality index can be
obtained through different sensors or monitoring stations based on which air pollution related health concerns can be predicted. In this
paper analysis was done on the dataset containing AQI of air pollutants such as NO2, O3, CO and SO2. The Random Forest algorithm
shows accuracy of 93.467% while the Multiclass classifier algorithm shows the accuracy of 94.61%. The results shown that Multiclass
classifier is better than the Random Forest algorithm.
关键词：Data Mining; Random Forest; Multiclass Classifier; Air Quality Index;
