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

F. Radmehr, N.S. Gharneh

Abstract


ENGLISH ABSTRACT: 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.

AFRIKAANSE OPSOMMING: Die navorsing handel oor n voorgestelde wasige vooruitskatting vir studente-inskrywing by die Universiteit van Alabama. n Nuwerwetse louter heuristiese simulasie-algoritme word gebruik. Die model word onder andere beheer deur n Taguchi optimiseringstegniek. Die modelresultate toon n verbetering op ander bestaande metodes.


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DOI: https://doi.org/10.7166/23-2-339

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