引用本文:方正,张磊,王玉琴,黄雅琨,徐静.基于自回归GA-BP神经网络的AQI预测[J].环境监控与预警,2019,11(2):22-25
FANG Zheng,ZHANG Lei,WANG Yu qin,HUANG Ya kun,XU Jing.An Autoregressive GA BP Neural Network based AQI Prediction[J].Environmental Monitoring and Forewarning,2019,11(2):22-25
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基于自回归GA-BP神经网络的AQI预测
方正,张磊,王玉琴,黄雅琨,徐静
徐州工程学院机电工程学院,江苏 徐州 221018
摘要:
基于徐州市2013年12月—2018年11月的空气质量指数日均值,建立了时间序列自回归输入的GA-BP神经网络模型用于空气质量指数预测。结果表明,所建立的网络模型能够准确预测徐州市空气质量指数的变化趋势,其中夏季预测相对误差18.23%,仿真均方根误差(RMSE)为14.59;冬季预测相对误差9.14%,仿真RMSE为11.47。
关键词:  自回归输入  GA-BP神经网络  空气质量指数
DOI:
分类号:TP183;X831
文献标识码:B
基金项目:大学生实践创新训练计划基金资助项目(xcx2018107)
An Autoregressive GA BP Neural Network based AQI Prediction
FANG Zheng,ZHANG Lei,WANG Yu qin,HUANG Ya kun,XU Jing
School of Mechanical & Electrical Engineering, Xuzhou University of Technology, Xuzhou,Jiangsu 221018,China
Abstract:
Based on the daily average of air quality index in Xuzhou from December 2013 to November 2018, this paper established a GA BP neural network model with autoregressive input of time series for air quality index prediction. The experimental results showed that the established network model could accurately predict the change trend of Xuzhou air quality index. The relative error of summer forecast was 18.23%, the simulation RMSE was 14.59, the winter forecast relative error was 9.14%, and the simulation RMSE was 11.47.
Key words:  Autoregressive inputs  GA BP neural network  Air quality index