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Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting

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Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting. / Egrioglu, Erol; Bas, Eren; Yolcu, Ufuk.
In: Granular Computing, Vol. 6, No. 3, 31.07.2021, p. 619-629.

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Egrioglu E, Bas E, Yolcu U. Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting. Granular Computing. 2021 Jul 31;6(3):619-629. Epub 2020 Mar 17. doi: 10.1007/s41066-020-00220-8

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Egrioglu, Erol ; Bas, Eren ; Yolcu, Ufuk. / Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting. In: Granular Computing. 2021 ; Vol. 6, No. 3. pp. 619-629.

Bibtex

@article{ea607a7f88bd4e38b90f533d4a02e2f9,
title = "Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting",
abstract = "Fuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems. In recent years, intuitionistic fuzzy sets have been preferred in the fuzzy modeling and new fuzzy inference systems have been proposed based on intuitionistic fuzzy sets. In this paper, a new intuitionistic fuzzy regression functions approach is proposed based on intuitionistic fuzzy sets for forecasting purpose. This new inference system is called an intuitionistic fuzzy time series functions approach. The contribution of the paper is proposing a new intuitionistic fuzzy inference system. To evaluate the performance of intuitionistic fuzzy time series functions, twenty-three real-world time series data sets are analyzed. The results obtained from the intuitionistic fuzzy time series functions approach are compared with some other methods according to a root mean square error and mean absolute percentage error criteria. The proposed method has superior forecasting performance among all methods.",
author = "Erol Egrioglu and Eren Bas and Ufuk Yolcu",
year = "2021",
month = jul,
day = "31",
doi = "10.1007/s41066-020-00220-8",
language = "English",
volume = "6",
pages = "619--629",
journal = "Granular Computing",
issn = "2364-4974",
publisher = "Springer",
number = "3",

}

RIS

TY - JOUR

T1 - Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting

AU - Egrioglu, Erol

AU - Bas, Eren

AU - Yolcu, Ufuk

PY - 2021/7/31

Y1 - 2021/7/31

N2 - Fuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems. In recent years, intuitionistic fuzzy sets have been preferred in the fuzzy modeling and new fuzzy inference systems have been proposed based on intuitionistic fuzzy sets. In this paper, a new intuitionistic fuzzy regression functions approach is proposed based on intuitionistic fuzzy sets for forecasting purpose. This new inference system is called an intuitionistic fuzzy time series functions approach. The contribution of the paper is proposing a new intuitionistic fuzzy inference system. To evaluate the performance of intuitionistic fuzzy time series functions, twenty-three real-world time series data sets are analyzed. The results obtained from the intuitionistic fuzzy time series functions approach are compared with some other methods according to a root mean square error and mean absolute percentage error criteria. The proposed method has superior forecasting performance among all methods.

AB - Fuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems. In recent years, intuitionistic fuzzy sets have been preferred in the fuzzy modeling and new fuzzy inference systems have been proposed based on intuitionistic fuzzy sets. In this paper, a new intuitionistic fuzzy regression functions approach is proposed based on intuitionistic fuzzy sets for forecasting purpose. This new inference system is called an intuitionistic fuzzy time series functions approach. The contribution of the paper is proposing a new intuitionistic fuzzy inference system. To evaluate the performance of intuitionistic fuzzy time series functions, twenty-three real-world time series data sets are analyzed. The results obtained from the intuitionistic fuzzy time series functions approach are compared with some other methods according to a root mean square error and mean absolute percentage error criteria. The proposed method has superior forecasting performance among all methods.

U2 - 10.1007/s41066-020-00220-8

DO - 10.1007/s41066-020-00220-8

M3 - Journal article

VL - 6

SP - 619

EP - 629

JO - Granular Computing

JF - Granular Computing

SN - 2364-4974

IS - 3

ER -