Show simple item record

dc.contributor.authorMeng, Dun
dc.contributor.authorXu, Zhicun
dc.contributor.authorWu, Lifeng
dc.contributor.authorYang, Yingjie
dc.date.accessioned2020-07-07T09:17:41Z
dc.date.available2020-07-07T09:17:41Z
dc.date.issued2020-03-26
dc.identifier.citationMeng, D., Xu, Z., Wu, L. and Yang, Y. (2020) Predict the particulate matter concentrations in 128 cities of China. Air Quality, Atmosphere & Health,13, pp. 399–407.en
dc.identifier.issn1873-9318
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/19942
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractTo predict the concentrations of PM2.5 and PM10 in the 128 cities of China, the discrete grey prediction model with fractional order accumulation (DFGM(1,1)) was used to predict the annual average PM2.5 and PM10 concentrations from 2019 to 2023. The result is as following: the annual average PM2.5 concentrations of Xi'an, Xuzhou, Ordos, Jingmen, Meizhou, Huizhou, Panzhihua, Kunming, Jixi and Yichun are increasing from 2019 to 2023. The annual average PM2.5 concentrations in the 118 other cities are decreasing from 2019 to 2023. While the annual average PM10 concentrations of Taiyuan, Ordos, Dongguan, Karamay, Foshan, Yichun, Qitaihe, Jinzhou and Heihe are increasing from 2019 to 2023. The annual average PM10 concentrations in the 119 other cities are decreasing from 2019 to 2023.en
dc.language.isoenen
dc.publisherSpringeren
dc.subjectPM2.5en
dc.subjectPM10en
dc.subjectgrey prediction model with fractional order accumulationen
dc.subjectbuffer operatorsen
dc.subjectGrey Wolf Optimizeren
dc.titlePredict the particulate matter concentrations in 128 cities of Chinaen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1007/s11869-020-00819-5
dc.peerreviewedYesen
dc.funderNo external funderen
dc.projectidIEC\NSFC\170391en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2020-03-19
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.funder.otherRoyal Societyen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record