摘要
随着中国经济的快速发展和城市人口的持续增长,大气环境急剧恶化,空气污染问题愈发严重。准确预测空气质量,及时采取有效防治措施显得尤为重要。本文基于西安市2020年1月至2021年12月空气质量指数日均值数据、空气质量等级以及同期气象数据,建立了PCA-SSA-Elman模型来预测西安市的空气质量指数。结果表明:PCA-SSA-Elman模型的MAPE仅为0.0255%,RMSE为3.0818,MAE为2.1491,误差指标评价值均小于其他对比模型,具有较高的拟合度和精确度。
With the rapid development of China's economy and the sustaining growth of urban population,the atmospheric environment has worsen sharply,and the air pollution trouble has become more and more severe.It is particularly vital to predict the air quality availably and take effective prevention measures timely.In this paper,PCA-SSA-Elman model is established to predict the air quality index of Xi'an city from January 2020 to December 2021 based on the daily mean data of air quality index,air quality grade and meteorological data of the same period.The results show that the MAPE of PCA-SSA-Elman model is only 0.0255%,RMSE is 3.0818,and MAE is 2.1491.The evaluation values of error indicators are all smaller than those of other comparison models,and it has high fitting degree and accuracy.
作者
张云飞
王万雄
ZHANG Yunfei;WANG Wanxiong(Gansu Agricultural University Faculty of Science,Lanzhou Gansu 730070)
出处
《软件》
2022年第6期30-34,共5页
Software
基金
国家自然科学基金(11971214)。
