Review on air pollution of Delhi zone using machine learning algorithm

Q3 Environmental Science
Anurag Sinha, Shubham Singh
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引用次数: 2

Abstract

The issue of pollution in urban cities is a major problem these days especially in cities like the New Delhi is detected with more number of toxic gases in air, which has deduced the air quality of New Delhi. Thus, predictive analytics play a significant role in predicting the future instances of air quality based on the historical data. Forecasting the air quality of these cities is mandatory to overcome its consequences. Several machines learning algorithm is widely used these days to predict the future instances. Such as random forest, support vector machine, regression, classification, and so on. Main pollutants which present in the air are PM2.5, PM10, CO, NO2, SO2 and O3. In this paper we have focused mainly on data set of New Delhi for predicting ambient air pollution and quality using several machines learning algorithm. A R T I C L E I N F O R M A T I O N Article Chronology: Received 25 October 2020 Revised 19 November 2020 Accepted 25 December 2020 Published 30 December 2020
基于机器学习算法的德里地区空气污染研究综述
城市的污染问题是一个主要问题,尤其是在像新德里这样的城市,空气中检测到更多的有毒气体,这推断了新德里的空气质量。因此,预测分析在根据历史数据预测未来空气质量方面发挥着重要作用。预测这些城市的空气质量是克服其后果的必要措施。目前,有几种机器学习算法被广泛用于预测未来的实例。如随机森林、支持向量机、回归、分类等。空气中存在的主要污染物是PM2.5、PM10、CO、NO2、SO2和O3。在本文中,我们主要关注新德里的数据集,使用几种机器学习算法来预测环境空气污染和质量。A R T I C L E I N F O R M A T I O N文章年代:2020年10月25日收稿2020年11月19日修稿2020年12月25日接受2020年12月25日发布2020年12月30日
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Air Pollution and Health
Journal of Air Pollution and Health Environmental Science-Global and Planetary Change
CiteScore
1.90
自引率
0.00%
发文量
36
审稿时长
8 weeks
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