English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51258/86283 (59%)
Visitors : 8018517      Online Users : 92
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99125


    Title: Tourism demand forecasting using a novel high-precision fuzzy time series model
    Authors: Tsaur, R.-C.;Kuo, T.-C.
    Contributors: 淡江大學管理科學學系
    Keywords: Fuzzy time series;Fourier series;Residual analysis;Japanese tourists;Fore- casting performance
    Date: 2014-04-01
    Issue Date: 2014-10-15 14:27:36 (UTC+8)
    Publisher: Kumamoto: I C I C International
    Abstract: Fuzzy time series model has been developed to either improve forecasting accuracy or reduce computation time, whereas a residul analysis in order to improve its forecasting performance is still lack of consideration. In this paper, we propose a novel Fourier method to revise the analysis of residual terms, and then we illustrate it to forecast the Japanese tourists visiting in Taiwan per year. The forecasting results show that our proposed method can derive the best forecasting performance as well as the smallest forecasting error of MAPE in the training sets; in the testing sets, the proposed model is also better to fit the future trend than some forecasting models.
    Relation: International Journal of Innovative Computing, Information and Control 10(2), pp.695-701
    Appears in Collections:[管理科學學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    Tourism demand forecasting using a novel high-precision fuzzy time series model.pdf158KbAdobe PDF207View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback