An ARMA type fuzzy time series forecasting method based on particle swarm optimization

Egrioglu, Erol and Yolcu, Ufuk and Aladag, Cagdas Hakan and Kocak, Cem (2013) An ARMA type fuzzy time series forecasting method based on particle swarm optimization. Mathematical Problems in Engineering, 2013. ISSN 1024-123X

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Abstract

In the literature, fuzzy time series forecasting models generally include fuzzy lagged variables. Thus, these fuzzy time series models have only autoregressive structure. Using such fuzzy time series models can cause modeling error and bad forecasting performance like in conventional time series analysis. To overcome these problems, a new first-order fuzzy time series which forecasting approach including both autoregressive and moving average structures is proposed in this study. Also, the proposed model is a time invariant model and based on particle swarm optimization heuristic. To show the applicability of the proposed approach, some methods were applied to five time series which were also forecasted using the proposed method. Then, the obtained results were compared to those obtained from other methods available in the literature. It was observed that the most accurate forecast was obtained when the proposed approach was employed.

Item Type:
Journal Article
Journal or Publication Title:
Mathematical Problems in Engineering
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200
Subjects:
ID Code:
139543
Deposited By:
Deposited On:
17 Dec 2019 09:30
Refereed?:
Yes
Published?:
Published
Last Modified:
24 Mar 2020 09:04