An adaptive forecast combination approach based on meta intuitionistic fuzzy functions

Tak, Nihat and Egrioglu, Erol and Bas, Eren and Yolcu, Ufuk (2021) An adaptive forecast combination approach based on meta intuitionistic fuzzy functions. Journal of Intelligent and Fuzzy Systems, 40 (5). pp. 9567-9581. ISSN 1064-1246

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Abstract

Intuitionistic meta fuzzy forecast combination functions are introduced in the paper. There are two challenges in the forecast combination literature, determining the optimum weights and the methods to combine. Although there are a few studies on determining the methods, there are numerous studies on determining the optimum weights of the forecasting methods. In this sense, the questions like 'What methods should we choose in the combination?' and 'What combination function or the weights should we choose for the methods' are handled in the proposed method. Thus, the first two contributions that the paper aims to propose are to obtain the optimum weights and the proper forecasting methods in combination functions by employing meta fuzzy functions (MFFs). MFFs are recently introduced for aggregating different methods on a specific topic. Although meta-analysis aims to combine the findings of different primary studies, MFFs aim to aggregate different methods based on their performances on a specific topic. Thus, forecasting is selected as the specific topic to propose a novel forecast combination approach inspired by MFFs in this study. Another contribution of the paper is to improve the performance of MFFs by employing intuitionistic fuzzy c-means. 14 meteorological datasets are used to evaluate the performance of the proposed method. Results showed that the proposed method can be a handy tool for dealing with forecasting problems. The outstanding performance of the proposed method is verified in terms of RMSE and MAPE.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Intelligent and Fuzzy Systems
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1702
Subjects:
ID Code:
174171
Deposited By:
Deposited On:
04 Aug 2022 15:55
Refereed?:
Yes
Published?:
Published
Last Modified:
04 Aug 2022 15:55