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
