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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/41946

Title: Application of fuzzy regression on air cargo volume forecast
Authors: Tsung-Yu Chou;Gin-Shuh Liang;Tzeu-Chen Han
Contributors: 國立臺灣海洋大學:航運管理學系
Keywords: Air cargo;Freight forecasting;Fuzzy linear regression;Index of optimism
Date: 2011-10
Issue Date: 2017-04-17T03:25:00Z
Publisher: Quality & Quantity
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.
Relation: 45(6) pp.1539-1550
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/41946
Appears in Collections:[航運管理學系] 期刊論文

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