Heuristic models of fuzzy time series for forecasting

Song and Chissom first proposed the definitions of fuzzy time series and time-invariant and variant models of fuzzy time series. Chen then proposed arithmetic operations to replace the complex computations in Song and Chissom's models. This study proposes heuristic models by integrating problem-specific heuristic knowledge with Chen's model to improve forecasting. This is because Chen's model was easy to calculate, was straightforward to integrate heuristic knowledge, and forecast better than the others. Both university enrollment and futures index are chosen as the forecasting targets. The empirical analyses show that the heuristic models reflect the fluctuations in fuzzy time series better and provide better overall forecasting results than the previous models. (C) 2001 Elsevier Science B.V. All rights reserved.