基于多维多步长LSTM网络的区域AQI预测研究  

Research on regional AQI prediction based on multi-dimensional and multi-step LSTM network

作　　者：刘颖 陈旭东[2] 周觅 郑乃瑞 陈元橼 LIU Ying;CHEN Xudong;ZHOU Mi;ZHENG Nairui;CHEN Yuanyuan(Faculty of Geosciences and Environmental Engineering,Southwest Jiaotong University,Chengdu 610031,China;不详)

机构地区：[1]西南交通大学地球科学与环境工程学院,成都610031 [2]重庆工商大学计算机科学与信息工程学院,重庆400067 [3]重庆高新区飞马创新研究院,重庆400051

出　　处：《工业安全与环保》2022年第10期100-103,共4页Industrial Safety and Environmental Protection

基　　金：国家自然科学基金(51779211);四川省科技计划项目(2019YJ02333)。

摘　　要：现有空气质量预测方法未同时考虑前期空气质量和气象影响,不能有效体现空气质量的时空依赖性。研究采集2017—2020年重庆市历史气象信息和历史空气质量数据,通过皮尔逊相关性分析,筛选重要的输入变量,构建基于多维多步长LSTM的重庆市空气质量预测模型,并与其他预测模型进行对比分析。结果表明:重庆市AQI与PM_(2.5)、PM_(10)有非常强的正相关性,与能见度、平均温度、湿度、降水量呈较强的负相关性;前7 d的空气质量状态和气象状态对空气质量预测有显著影响,能更准确的预测AQI值。预测损失均方根误差为12.206,平均绝对误差为9.430。The existing air quality prediction methods do not consider the influence of previous air quality state and meteorological state at the same time,and can not reflect the spatial and temporal dependence of air quality effectively.The historical meteorological elements and historical air quality index(AQI)of Chongqing during 2017 to 2020 were collected.Through Pearson correlation analysis of characteristic variables,important input variables were screened out.The air quality prediction model of Chongqing based on multi-dimensional and multi-step LSTM was established and compared with other prediction models.The results show that AQI in Chongqing has a very strong positive correlation with PM_(2.5) and PM_(10),and a strong negative correlation with visibility,average temperature,humidity and precipitation.The air quality state and meteorological state in the first 7 days have a significant impact on the air quality,and can predict the AQI value more accurately.The root mean square error of loss prediction is 12.206,and the mean absolute error is 9.430.

关 键 词：多维多步长 LSTM AQI 空气质量预测模型 

分 类 号：X51[环境科学与工程—环境工程]