摘要
机场源NOx是机场范围内的首要空气污染物,显著影响机场空气质量.基于FGM(r,1)模型,利用周因子建立FGWM(r,1)模型,分析并预测南京禄口国际机场起降航空器的发动机在LTO循环内的NO_(x)排放量,对比FGM(r,1)模型和FGWM(r,1)模型的预测效果,利用HW季节预测模型验证.研究结果表明,FGWM(r,1)模型的预测效果虽呈现周特性,但其平均相对预测误差绝对值较FGM(r,1)约高1.40%,较HW季节预测模型约低8.49%.此外,FGWM(r,1)模型的平均相对预测误差绝对值随X^((0))波动程度的增大而增大.
Airport-sourced NO_(x) is the primary air pollutant within the airport,which significantly affects airport air quality.Based on the FGM(r,1),the FGWM(r,l) is established by using weekly factors to analyze and predict the NO_(x) emissions of the engines serviced at the Nanjing Lukou International Airport during the LTO cycle.The prediction effect of the FGM(r,l) and FGWM(r,l) are compared,which is verified by the HW seasonal prediction model.The research results show that although the prediction effect of the FGWM(r,l) shows weekly characteristics,its mean absolute percentage error is about 1.40% higher than that of the FGM(r,l),and about 8.49% lower than the HW seasonal prediction model.In addition,the mean absolute percentage error of the FGWM(r,l) increases with the fluctuation degree of X^((0)).
作者
王湛
张耀
于女
张梦雅
WANG Zhan;ZHANG Yao;YU NU;ZHANG Meng-ya(College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处
《数学的实践与认识》
2021年第15期84-93,共10页
Mathematics in Practice and Theory
基金
江苏省科研与实践创新计划项目基金(SJCX20-0067)
南京航空航天大学新教师启动基金(90YAH19018)。
