Fuzzy Autoregressive Time Series Model Based on Symmetry Triangular Fuzzy Numbers
Riswan Efendi,
Adhe N. Imandari,
Yusnita Rahmadhani,
Suhartono,
Noor A. Samsudin,
Nureize Arbai and
Mustafa M. Deris
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Riswan Efendi: Mathematics Department, Faculty of Sciences and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Perak, Malaysia
Adhe N. Imandari: #x2020;Mathematics Department, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau, 28294 Panam, Pekanbaru, Indonesia
Yusnita Rahmadhani: #x2020;Mathematics Department, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau, 28294 Panam, Pekanbaru, Indonesia
Suhartono: #x2021;Department of Statistics, Faculty of Mathematics Computing and Data Science, Institut Teknologi Sepuluh Nopember, 60111 Surabaya, Indonesia
Noor A. Samsudin: #xA7;Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
Nureize Arbai: #xA7;Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
Mustafa M. Deris: #xB6;Faculty Applied Science and Technology, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, Malaysia
New Mathematics and Natural Computation (NMNC), 2021, vol. 17, issue 02, 387-401
Abstract:
The symmetry triangular fuzzy number has been developed to build fuzzy autoregressive models by using various approaches such as low-high data, integer number, measurement error, and standard deviation data. However, most of these approaches are not simulated and compared between ordinary least square and fuzzy optimization in parameter estimation. In this paper, we are interested in implementation of measurement error and standard deviation data in construction symmetry triangular fuzzy numbers. Additionally, both types of triangular fuzzy numbers are deployed to build a fuzzy autoregressive model, especially the second order. The simulation result showed that the fuzzy autoregressive model produced the smaller mean square error and average width if compared with the ordinary autoregressive model. In the implementation, the high accuracy was also achieved by the fuzzy autoregressive model in consumer goods stock prediction. From the simulation and implementation, the proposed fuzzy autoregressive model is a competent approach for upper and lower forecasts.
Keywords: Fuzzy autoregressive; symmetry triangular fuzzy number; measurement error; standard deviation; narrow interval (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:nmncxx:v:17:y:2021:i:02:n:s1793005721500204
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DOI: 10.1142/S1793005721500204
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