title: Estimating air quality in a traffic tunnel using a forecasting combination model.
abstract: This study compared three forecasting methods based on their accuracy or absolute errors in forecasting air pollution in a traffic tunnel: the Grey model (GM), the Crank-Nicholson implicit scheme model, and the forecasting combination model (FCM). Three criteria, root mean square error (RMSE), the mean absolute error (MAE) and mean absolute percentage error (MAPE), were applied to the models and the FCM model displayed all of the characteristics of a good forecasting model. The correlation coefficient (r) for the FCM model equaled 0.94 (Upwind), 0.98 (Middle) and 0.98 (Downwind). This study indicated that FCM can be used to accurately forecast CO pollution in the Kaohsiung Cross Harbor Tunnel.
authors.affiliation: Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, Taiwan.
authors.forename: Cheng-Chung
authors.initials: CC
authors.lastname: Lee
authors.forename: Terng-Jou
authors.initials: TJ
authors.lastname: Wan
authors.forename: Chao-Yin
authors.initials: CY
authors.lastname: Kuo
authors.forename: Chung-Yi
authors.initials: CY
authors.lastname: Chung
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D005544:Forecasting; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D013997:Time Factors; D014691:Ventilation
chemical_list: D000393:Air Pollutants