Improved grey prediction models for the trans‐pacific air passenger market

淡江大學機構典藏 > 商管學院 > 運輸管理學系暨研究所 > 期刊論文 > Item 987654321/62118

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题名:	Improved grey prediction models for the trans‐pacific air passenger market
作者:	Hsu, Chaug-ing;溫裕弘;Wen, Yuh-horng;Hsu, Chaug-ing
贡献者:	淡江大學運輸管理學系
关键词:	Grey theory;Grey model (GM);Air passenger traffic;Accumulated generating operation (AGO);Prediction
日期:	1998-01-01
上传时间:	2011-10-17 22:37:49 (UTC+8)
摘要:	The rapid economic growth of Asia‐Pacific countries continues to result in faster travel growth in the trans‐Pacific air passenger market. Grey theory is used to develop time series GM(1,1) models for forecasting total passenger and 10 country‐pair passenger traffic flows in this market. The accumulated generating operation (AGO) is one of the most important characteristics of grey theory, and its main purpose is to reduce the randomness of data. The original GM(1,1) models are improved by using residual modifications with Markov‐chain sign estimations. These models are shown to be more reliable by posterior checks and to yield more accurate prediction results than ARIMA and multiple regression models. The results indicate that the total number of air passengers in the trans‐Pacific market will increase at an average annual growth rate of approximately 11% up to the year 2000.
關聯:	Transportation planning and technology 22(2), pp.87-107
DOI:	10.1080/03081069808717622
显示于类别:	[運輸管理學系暨研究所] 期刊論文

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