Prediction of local particle pollution level based on artificial neural network

Prediction of local particle pollution level based on artificial neural network

Citizens eager to know the local pollution level to prevent from air pollution. The real-time measurement for everywhere is a very expensive way, a statistical model based on artificial neural network is applied in this research. This model can estimate particle pollution level with some influencing...

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Bibliographic Details
Main Authors: Xiong Jie, Yao Runming, Li Baizhan
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/37/e3sconf_clima2019_02031.pdf
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spelling doaj-c569f90807a445f38bab7b9a398e33ee2021-04-02T11:08:09ZengEDP SciencesE3S Web of Conferences2267-12422019-01-011110203110.1051/e3sconf/201911102031e3sconf_clima2019_02031Prediction of local particle pollution level based on artificial neural networkXiong JieYao RunmingLi BaizhanCitizens eager to know the local pollution level to prevent from air pollution. The real-time measurement for everywhere is a very expensive way, a statistical model based on artificial neural network is applied in this research. This model can estimate particle pollution level with some influencing factors, including background pollution level, weather conditions, urban morphology and local pollution sources. The monitoring from regulatory monitoring sites is considered as the background level. The field measurements of 20 locations are conducted to feed the output layer of ANN model. The average relative error of prediction compared with measurement is 9.24% for PM10 and 18.90% for PM2.5.https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/37/e3sconf_clima2019_02031.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Xiong Jie
Yao Runming
Li Baizhan
spellingShingle Xiong Jie
Yao Runming
Li Baizhan
Prediction of local particle pollution level based on artificial neural network
E3S Web of Conferences
author_facet Xiong Jie
Yao Runming
Li Baizhan
author_sort Xiong Jie
title Prediction of local particle pollution level based on artificial neural network
title_short Prediction of local particle pollution level based on artificial neural network
title_full Prediction of local particle pollution level based on artificial neural network
title_fullStr Prediction of local particle pollution level based on artificial neural network
title_full_unstemmed Prediction of local particle pollution level based on artificial neural network
title_sort prediction of local particle pollution level based on artificial neural network
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2019-01-01
description Citizens eager to know the local pollution level to prevent from air pollution. The real-time measurement for everywhere is a very expensive way, a statistical model based on artificial neural network is applied in this research. This model can estimate particle pollution level with some influencing factors, including background pollution level, weather conditions, urban morphology and local pollution sources. The monitoring from regulatory monitoring sites is considered as the background level. The field measurements of 20 locations are conducted to feed the output layer of ANN model. The average relative error of prediction compared with measurement is 9.24% for PM10 and 18.90% for PM2.5.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/37/e3sconf_clima2019_02031.pdf
work_keys_str_mv AT xiongjie predictionoflocalparticlepollutionlevelbasedonartificialneuralnetwork
AT yaorunming predictionoflocalparticlepollutionlevelbasedonartificialneuralnetwork
AT libaizhan predictionoflocalparticlepollutionlevelbasedonartificialneuralnetwork
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