The Forecasting Efficiency of Fuzzy Time Series Model Based on Fuzzy Inverse for Forecasting Thailand Fruit Price

Abstract

Fuzzy time series model based on fuzzy inverse and SARIMA model were applied for forecasting Tubtim Chandra Rose Apple and Shogun Orange prices in Thailand in different seasons, and the data gained from the study is uncertain. As a result of data uncertainty, the accuracy of two methods was compared by the mean absolute percentage error (MAPE). The results show that the forecast values by the modified fuzzy time series forecasting method is more accurate than the SARIMA model.