Abstract
In many forecasting models using fuzzy approach, discrete fuzzy sets were used as a basis for calculating the forecasted values. However, these types of models cannot provide the forecasted ranges under different degree of confidence. In this paper, a hybrid fuzzy approach which combines the hypothesis test, natural partition method, trapezoidal fuzzy numbers (TFNs) concept and heuristic rules is proposed. The hypothesis test is used for determining the trend and seasonal pattern, natural partitioning method for determining the interval length, TFNs for representing the linguistic values and heuristic rule for obtaining the forecasted values. The tourist arrivals to Sarawak Malaysia during January 2007 to December 2012 were employed as data set. The result shows that the data have only seasonal pattern with no trend pattern. 17 linguistic values in terms of TFNs have been generated. The forecasted ranges under different degree of confidence can be obtained. The proposed hybrid fuzzy approach can cater for trend and seasonal time series data, and can produce forecasted ranges under different degree of confidence which can provide more information on the forecasted values.
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