:: Volume 1, Issue 2 (8-2014) ::
2014, 1(2): 152-166 Back to browse issues page
The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination
Liangping Wu * 1, Jian Zhang2
1- College of Mathematics and Software Science, Sichuan Normal University, Chengdu, China. , wuliangping6@sina.com
2- Visual Computing and Virtual Reality Key Laboratory of Sichuan Province, Sichuan Normal University, Chengdu, China.
Abstract:   (7351 Views)
Three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted MSFE method. These methods assign the different weights that can not change at each time point to each individual forecasting model. In this study, we introduce the IOWGA operator combination method which can overcome the defect of previous three combination methods into tourism forecasting. Moreover, we further investigate the performance of the four combination methods through the theoretical evaluation and the forecasting evaluation. The results of the theoretical evaluation show that the IOWGA operator combination method obtains extremely well performance and outperforms the other forecast combination methods. Furthermore, the IOWGA operator combination method can be of well forecast performance and performs almost the same to the variance-covariance combination method for the forecasting evaluation. The IOWGA operator combination method mainly reflects the maximization of improving forecasting accuracy and the variance-covariance combination method mainly reflects the decrease of the forecast error. For future research, it may be worthwhile introducing and examining other new combination methods that may improve forecasting accuracy or employing other techniques to control the time for updating the weights in combined forecasts.
Keywords: Tourism forecasts, Forecast combination, IOWGA operator, Theoretical evaluation, Forecasting evaluation
     
Type of Study: مقاله پژوهشی |
ePublished: 2017/09/28


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Volume 1, Issue 2 (8-2014) Back to browse issues page