Abstract
This paper presented a Fuzzy Regression Forecasting Model (FRFM) to forecast demand by examining present international air cargo market. Accuracy is one of the most important concerns when dealing with forecasts. However, there is one problem that is often overlooked. That is, an accurate forecast model for one does not necessarily suit the other. This is mainly due to individual’s different perceptions toward their socioeconomic environment as well as their competitiveness when evaluating risk. Therefore people make divergent judgments toward various scenarios. Yet even when faced with the same challenge, distinctive responses are generated due to individual evaluations in their strengths and weaknesses. How to resolve these uncertainties and indefiniteness while accommodating individuality is the main purpose of constructing this FRFM. When forecasting air cargo volumes, uncertainty factors often cause deviation in estimations derived from traditional linear regression analysis. Aiming to enhance forecast accuracy by minimizing deviations, fuzzy regression analysis and linear regression analysis were integrated to reduce the residual resulted from these uncertain factors. The authors applied α-cut and Index of Optimism λ to achieve a more flexible and persuasive future volume forecast.
Similar content being viewed by others
References
Anonymous: A Study on Civil Aviation Development in Taiwan Area. Institute of Transportation Ministry of Transportation and Communications. http://www.motc.gov.tw/motchypage/hypage.cgi?YPAGE=yearbook.asp&mp=1, Dec (1996)
Chen, C.Y.: Analyzing and forecasting freight transportation market in cross-strait direct shipping. Master Thesis, National Cheng Kung University, Taiwan (1998)
Dubois D., Prade H.: Operations in fuzzy numbers. Int. J. Syst. Sci. 9, 613–626 (1978)
Greene W.H.: Econometric Analysis. Prentice Hall, Upper Saddle River (2003)
Hamoen, F.A.M.: Combination carriers and a dedicated air cargo hub-and-spoke network. http://www.tiaca.org./researchpapers/hamoen.html (1999)
Hsu C.I., Wen Y.H.: Applying grey forecasting models to predict international air travel demand for Taiwan area. Transp. Plan. J. 26(3), 525–556 (1997)
Liang G.S., Han T.C., Chou T.Y: Using a fuzzy quality function deployment model to identify airport cargo terminal improvement points. Transp. Res. Rec. 1935, 130–140 (2005)
Lin, G.K.: The Study of forecast of container traffic by ports in Taiwan area. Master Thesis, National Taiwan Ocean University, Taiwan (2000)
Profillidis V.A.: Econometric and fuzzy model for the forecast of demand in the air port of Rhode. J. Air Transp. Manag. 6, 95–100 (2000)
RITA: The Changing Face of Transportation. http://www.bts.gov/publications/the_changing_face_of_transportation/chapter_04.html (2000)
Su, C.C.: Forecasting the freight of Taichung port import and export cargo. Master Thesis, National Taiwan Ocean University, Taiwan (1998)
Tanaka H., Vejima S., Asai K.: Linear regression analysis with fuzzy model. IEEE Trans. Syst. Man Cybern. 12, 903–907 (1982)
Wells A.T.: Air Transportation: A Management Perspective. Wadsworth publishing Company, Belmont (1998)
Zadeh L.A.: Fuzzy sets. Inf. Control 3, 338–353 (1965)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chou, TY., Liang, GS. & Han, TC. Application of fuzzy regression on air cargo volume forecast. Qual Quant 47, 897–908 (2013). https://doi.org/10.1007/s11135-011-9572-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11135-011-9572-4