The Study of Forecasting Models for the Numbers of Tour Bus Passengers in Taiwan

• Main Authors: Jyan-Yuan Huang, 黃俊源
• Other Authors: Ying-Fang Huang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/78475504244848558186

碩士 === 國立高雄應用科技大學 === 工業工程與管理系碩士班 === 102 === Progress of the times and technology, Pipeline between countries is very convenient. With the policy after another mainland tourists travel to Taiwan. The domestic tourism market because of rising per capita income and the related policies weekends, people pay attention to the needs of leisure activities and sightseeing tours are also rapidly rising. Taiwan tour bus belonging to the tourism industry of passenger transport, road travel is the preferred means of transport. One important tool is also a land mass transportation, driving under the tourism industry, enhance the added value and economic benefit tour industry. Therefore, this study will explore the predictive models in Taiwan, followed by a manned research tour ride, hoping to find a feasible and accurate predictive models. Tour industry to make changes in the market demand can be more accurate and perfect, the main motivation for this study explored in depth. Research ranges from 2009 to 2012 Taiwan tour multiplied manned times. Application of gray theory GM (1,1) model and the traditional forecasting methods exponential smoothing, simple linear regression to do predictive analysis. Reuse mean absolute percentage error to measure the performance and accuracy of the model, to find the best predictive model. The results showed that, MAPE GM (1,1) model was 10.55%, with an accuracy of 89.45%, both better than the exponential smoothing MAPE was 25.36%, with an accuracy of 74.64%, and the simple linear regression MAPE was 15.21%, the precise degree is 84.79%Finally, studies using GM (1,1) model to speculate 2013-2015 Taiwan and manned by regional tour, followed by demand trends, as a reference for the domestic tour industry and academic researchers.