Dear users,
This is our new website
(we are launching the new one in order to improve our communication and provide better services to the editors and authors. So we will upload all data soon).


Please click here to visit our current website, and also to submit your paper
:
 
www.ijsom.com 


 Thanks for your patience during relocation.

Feel free to contact us via info@ijsom.com and ijsom.info@gmail.com

   [Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
Indexing Databases

AWT IMAGE
AWT IMAGE

AWT IMAGE

AWT IMAGE

AWT IMAGE

AWT IMAGE

AWT IMAGE

AWT IMAGE

AWT IMAGE

..
:: Search published articles ::
Showing 1 results for Forecasting Evaluation

Liangping Wu, Jian Zhang,
Volume 1, Issue 2 (8-2014)
Abstract

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.

Page 1 from 1     

International Journal of Supply and Operations Management International Journal of Supply and Operations Management
Persian site map - English site map - Created in 0.06 seconds with 29 queries by YEKTAWEB 4666