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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/77286

    Title: The adaptive fuzzy time series model with an application to Taiwan's tourism demand
    Authors: Tsaur, Ruey-chyn;Kuo, Ting-chun
    Contributors: 淡江大學管理科學學系
    Keywords: Adaptive fuzzy time series model;Forecasting;Fuzzy logic group;Tourism demand
    Date: 2011-08
    Issue Date: 2012-06-14 10:32:58 (UTC+8)
    Publisher: Kidlington: Pergamon
    Abstract: In this study, an adaptivefuzzytimeseriesmodel for forecasting Taiwan’stourismdemand is proposed to further enhance the predicted accuracy. We first transfer fuzzytimeseries data to the fuzzy logic group, assign weights to each period, and then use the proposed adaptivefuzzytimeseriesmodel for forecasting in which an enrollment forecasting values is applied to obtain the smallest forecasting error. Finally, an illustrated example for forecasting Taiwan’stourismdemand is used to verify the effectiveness of proposed model and confirmed the potential benefits of the proposed approach with a very small forecasting error MAPE and RMSE.
    Relation: Expert Systems with Applications 38(8), pp.9164-9171
    DOI: 10.1016/j.eswa.2011.01.059
    Appears in Collections:[Department of Management Sciences] Journal Article

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