{"title":"基于时间序列分析模型的哈尔滨市环境空气质量预测与分析","authors":"Zhihao Zhang, Yanan Li, Jiazhuo Qi, Jun-jian Ma, Xiaoyan Wang, Miao Zhou","doi":"10.1109/ICESGE56040.2022.10180313","DOIUrl":null,"url":null,"abstract":"To grasp the future trend of ambient air quality more accurately and provide more reliable data support for formulating and implementing environmental protection departments' policies. This paper establishes the Winters model and mean GM (1,1) model to predict the ambient air quality in the next five years, based on Harbin's atmospheric environmental quality monitoring data from 2015 to 2021. The results show that the seasonal characteristics of ambient air quality in Harbin are still not eliminated, but the overall trend is improving year by year. Using the combined model can make long-term predictions for smaller time units, enhancing work precision and short-term predictions for larger time units. Furthermore, it makes the comprehensive study and judgment of the future change trend of environmental factors more reasonable and the prediction results more meaningful.","PeriodicalId":120565,"journal":{"name":"2022 International Conference on Environmental Science and Green Energy (ICESGE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction and Analysis of Ambient Air Quality in Harbin Based on Time Series Analysis Model\",\"authors\":\"Zhihao Zhang, Yanan Li, Jiazhuo Qi, Jun-jian Ma, Xiaoyan Wang, Miao Zhou\",\"doi\":\"10.1109/ICESGE56040.2022.10180313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To grasp the future trend of ambient air quality more accurately and provide more reliable data support for formulating and implementing environmental protection departments' policies. This paper establishes the Winters model and mean GM (1,1) model to predict the ambient air quality in the next five years, based on Harbin's atmospheric environmental quality monitoring data from 2015 to 2021. The results show that the seasonal characteristics of ambient air quality in Harbin are still not eliminated, but the overall trend is improving year by year. Using the combined model can make long-term predictions for smaller time units, enhancing work precision and short-term predictions for larger time units. Furthermore, it makes the comprehensive study and judgment of the future change trend of environmental factors more reasonable and the prediction results more meaningful.\",\"PeriodicalId\":120565,\"journal\":{\"name\":\"2022 International Conference on Environmental Science and Green Energy (ICESGE)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Environmental Science and Green Energy (ICESGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICESGE56040.2022.10180313\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Environmental Science and Green Energy (ICESGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICESGE56040.2022.10180313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction and Analysis of Ambient Air Quality in Harbin Based on Time Series Analysis Model
To grasp the future trend of ambient air quality more accurately and provide more reliable data support for formulating and implementing environmental protection departments' policies. This paper establishes the Winters model and mean GM (1,1) model to predict the ambient air quality in the next five years, based on Harbin's atmospheric environmental quality monitoring data from 2015 to 2021. The results show that the seasonal characteristics of ambient air quality in Harbin are still not eliminated, but the overall trend is improving year by year. Using the combined model can make long-term predictions for smaller time units, enhancing work precision and short-term predictions for larger time units. Furthermore, it makes the comprehensive study and judgment of the future change trend of environmental factors more reasonable and the prediction results more meaningful.