FORECASTING METHOD BASED ON HIGH ORDER FUZZY TIME SERIES AND SIMULATED ANNEALING TECHNIQUE

This paper proposes a fuzzy forecasting problem to forecast the Alabama University enrolment dataset. A novel simulated annealing heuristic algorithm is used to promote the accuracy of forecasting. The algorithm enjoys two new neighbourhood search operators called 'subtitle' and 'adjust'. A Taguchi method is also used as an optimisation technique to tune the different parameters and operators of the proposed model comprehensively. The experimental results show that the proposed model is more accurate than existing models.