摘要
为提高中国入境旅游人数月度数据序列预测精度,文章选择了目前相对最优单项预测模型——TRAMO/SEATS短记忆预测模型和ARFIMA长记忆预测模型,并根据中国入境旅游人数月度数据序列特点,采用非常适合中国入境旅游人数月度数据序列预测并具有高预测精度的传统线性回归预测模型,然后将各个单项预测模型进行基于IOWHA算子的组合。研究发现:基于IOWHA算子的组合预测模型,达到了目前为止中国入境旅游人数月度数据序列预测的最高精度。最后,根据中国入境旅游人数实际值和组合模型预测值的比较,定量分析世界金融危机等事件对中国入境旅游的影响程度和影响时滞,并探究中国入境旅游未来的发展趋势。
In order to improve the forecast precision of monthly data of China＇s inbound tourists,we choose currently the most relatively superior monomial forecast model—TRAMO/SEATS short memory forecast model and ARFIMA long memory forecast model and adopt traditional linear forecast model that is most suitable for forecasting monthly data of China＇s inbound tourists to combine each monomial forecast model based on IOWHA operator.The results show that combined forecast model that the paper establishes based on IOWHA operator has achieved the highest forecast precision of monthly data of China＇s inbound tourists so far.Finally,the paper in accordance with the comparison between actual value of China＇s inbound tourists and prediction of combined model value,makes a quantitative analysis of the impact degree and time lag of world financial crisis and other events on China＇s inbound tourism and probe into the future tendency for developing China＇s inbound tourism.
出处
《旅游学刊》
CSSCI
北大核心
2011年第11期19-27,共9页
Tourism Tribune
基金
国家自然科学基金(11071177)
可视化计算与虚拟现实四川省重点实验室项目(J2010N10)资助~~
关键词
入境旅游
IOWHA算子
组合预测
金融危机
应用分析
inbound tourism
IOWHA operator
combined forecast
financial crises
application and analysis
