Air quality secondary forecast model based on ARIMA time series model

被引：0

作者：

Yuan, Xiqian ^{[1
]}

Yang, Mengqi ^{[1
]}

Sun, Tingkun ^{[1
]}

Li, Xindong ^{[1
]}

机构：

[1] Qilu Univ Technol, Shandong Acad Sci, Sch Math & Stat, Jinan, Peoples R China

来源：

2023 3RD ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE, ACCTCS | 2023年

关键词：

air quality prediction; ARIMA; air quality index;

D O I：

10.1109/ACCTCS58815.2023.00093

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the further frequent of human living activities, natural meteorological changes will lead to some harmful substances into the atmosphere, the concentration of harmful substances is too high will harm people's health, air quality forecast can make people timely and effective response to bad air conditions In this paper, the concentrations of six common pollutants related to air quality are analyzed and predicted by combining existing air quality forecasting models and known data. The time series model is established and the secondary model is built on the basis of the original primary forecast, which improves the accuracy of air quality forecast.

引用

页码：310 / 313

页数：4