Abstract
In this study, seven types of first-order and one-variable grey differential equation model (abbreviated as GM (1, 1) model) were used to predict hourly ozone concentrations in Dali area of Taichung City, Taiwan. The results indicated that the minimum mean absolute percentage error (MAPE), mean squared error (MSE), root mean squared error (RMSE), and maximum correlation coefficient (R) were 19.00%, 45.27, 6.73, and 0.91, respectively. All statistical values revealed that the prediction performance of GM (1, 1, x(0)), GM (1, 1, a), and GM (1, 1, b) is better than the performance of other GM (1, 1) models. The GM (1, 1) model required a very small sample size, as low as four samples, but the modeling could result in very high prediction accuracy. It is also revealed that GM (1, 1) GM (1, 1) was an efficiently early warning tool to provide ozone information to inhabitants.
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Abdul-Wahab, S.A., Bakheit, C.S., Al-Alawi, S.M.: Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environmental Modelling and Software 20(10), 1263–1271 (2005)
Cai, M., Yin, Y., Xie, M.: Prediction of hourly air pollutant concentra-tions near urban arterials using artificial neural network approach. Transportation Research Part D: Transport and Environment 14, 32 (2009)
Cunningham, W.P., Cunningham, M.A.: Principles of Environmental Science. McGraw-Hill Company, New York (2006)
Deng, J.: The Foundation of Grey Theory. Huazhang University of Science and Technology Press, Wuhan (2002)
Deng, J.: The Primary Methods of Grey System Theory. Huazhang University of Science and Technology Press, Wuhan (2005)
Delucchi, M.A., Greene, D.L., Wang, M.Q.: Motor-vehicle fuel economy: The forgotten hydrocarbon control strategy. Transportation Research Part A: Policy and Practice 28(3), 223–244 (1994)
Faiz, A., Gautam, S., Burki, E.: Air pollution from motor vehicles: issues and options for Latin American countries. The Science of the Total Environment 169(1-3), 303–310 (1995)
Fischer, P.H., Hoek, G., van Reeuwijk, H., Briggs, D.J., Lebret, E., van Wijnen, J.H., Kingham, S.: Traffic-related differences in outdoor and indoor concentrations of particles and volatile organic compounds in Amsterdam. Atmospheric Environment 34(22), 3713–3722 (2000)
Gao, H.O.: Day of week effects on diurnal ozone/NOx cycles and transportation emissions in Southern California. Transportation Research Part D: Transport and Environment 12(4), 292–305 (2007)
Gao, H.O., Niemeier, D.A.: The impact of rush hour traffic and mix on the ozone weekend effect in southern California. Transportation Research Part D: Transport and Environment 12(2), 83–98 (2007)
Gautam, A.K., Chelani, A.B., Jain, V.K., Devotta, S.: A new scheme to predict chaotic time series of air pollutant concentrations using artificial neural network and nearest neighbor searching. Atmospheric Environment 42, 4409 (2008)
Kingham, S., Briggs, D., Elliott, P., Fischer, P., Erik, L.: Spatial variations in the concentrations of traffic-related pollutants in indoor and outdoor air in Huddersfield, England. Atmospheric Environment 34(6), 905–916 (2000)
Lipfert, F.W., Wyzga, R.E., Baty, J.D., Miller, J.P.: Traffic density as a surrogate measure of environmental exposures in studies of air pollution health effects: long-term mortality in a cohort of US veterans. Atmospheric Environment 40(1), 154–169 (2006)
Pai, T.Y., Hanaki, K., Ho, H.H., Hsieh, C.M.: Using grey system theory to evaluate transportation on air quality trends in Japan. Transportation Research Part D: Transport and Environ-ment 12(3), 158–166 (2007a)
Pai, T.Y., Tsai, Y.P., Lo, H.M., Tsai, C.H., Lin, C.Y.: Grey and neural network prediction of suspended solids and chemical oxygen demand in hospital wastewater treatment plant effluent. Computers & Chemical Engineering 31(10), 1272–1281 (2007b)
Pai, T.Y., Chiou, R.J., Wen, H.H.: Evaluating impact level of different factors in environmental impact assessment for incinerator plants using GM (1, N) model. Waste Management 28(10), 1915–1922 (2008a)
Pai, T.Y., Chuang, S.H., Ho, H.H., Yu, L.F., Su, H.C., Hu, H.C.: Predicting performance of grey and neural network in industrial effluent using online monitoring parameters. Process Biochemistry 43(2), 199–205 (2008b)
Pai, T.Y., Chuang, S.H., Wan, T.J., Lo, H.M., Tsai, Y.P., Su, H.C., Yu, L.F., Hu, H.C., Sung, P.J.: Comparisons of grey and neural network prediction of industrial park wastewater effluent using influent quality and online monitoring parameters. Environmental Monitoring and Assessment 146(1-3), 51–66 (2008c)
Pai, T.Y., Chang, T.C., Chen, H.H., Ouyang, C.F.: Using grey relation analysis to evaluate the reuse potential of municipal wastewater treatment plant effluent based on quality and quantity. Journal of Environmental Engineering and Management 20(2), 85–90 (2010)
Pai, T.Y., Lin, K.L., Shie, J.L., Chang, T.C., Chen, B.Y.: Predicting the co-melting temperatures of municipal solid waste incinerator fly ash and sewage sludge ash using grey model and neural network. Waste Management & Research (2011a) (in press)
Pai, T.Y., Ho, C.L., Chen, S.W., Lo, H.M., Sung, P.J., Lin, S.W., Lai, W.J., Tseng, S.C., Ciou, S.P., Kuo, J.L., Kao, J.T.: Using seven types of GM (1, 1) model to forecast hourly particulate matter concentration in Banciao City of Taiwan. Water, Air, and Soil Pollution 217(1-4), 25–33 (2011b)
Wang, G., Bai, S., Ogden, J.M.: Identifying contributions of on-road motor vehicles to urban air pollution using travel demand model data. Transportation Research Part D: Transport and Environment 14(3), 168–179 (2009)
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Pai, TY., Lin, SH., Yang, PY., Chang, DH., Kuo, JL. (2013). Predicting Hourly Ozone Concentration Time Series in Dali Area of Taichung City Based on Seven Types of GM (1, 1) Model. In: Pedrycz, W., Chen, SM. (eds) Time Series Analysis, Modeling and Applications. Intelligent Systems Reference Library, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33439-9_17
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