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ARIMA based Interval Type-2 Fuzzy Model for Forecasting

by Saima H., J. Jaafar, S. Belhaouari, T.A. Jillani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 3
Year of Publication: 2011
Authors: Saima H., J. Jaafar, S. Belhaouari, T.A. Jillani
10.5120/3369-4652

Saima H., J. Jaafar, S. Belhaouari, T.A. Jillani . ARIMA based Interval Type-2 Fuzzy Model for Forecasting. International Journal of Computer Applications. 28, 3 ( August 2011), 17-21. DOI=10.5120/3369-4652

@article{ 10.5120/3369-4652,
author = { Saima H., J. Jaafar, S. Belhaouari, T.A. Jillani },
title = { ARIMA based Interval Type-2 Fuzzy Model for Forecasting },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 3 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number3/3369-4652/ },
doi = { 10.5120/3369-4652 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:47.655494+05:30
%A Saima H.
%A J. Jaafar
%A S. Belhaouari
%A T.A. Jillani
%T ARIMA based Interval Type-2 Fuzzy Model for Forecasting
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 3
%P 17-21
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To solve the chaotic and uncertain problems, researchers are focusing on the extensions of classical fuzzy model. At present Interval Type-2 Fuzzy logic Systems (IT2-FLS) are extensively used after the thriving exploitation of Type-2 FLS. Fuzzy time series models have been used for forecasting stock and FOREX indexes, enrollments, temperature, disease diagnosing and weather. In this paper a hybrid fuzzy time series model is proposed that will develop an Interval type 2 fuzzy model based on ARIMA. The proposed model will use ARIMA to select appropriate coefficients from the observed dataset. IT2-FLS is utilized here for handling the uncertainty in the time series data so that it may yield a more accurate forecasting result.

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Index Terms

Computer Science
Information Sciences

Keywords

Type-1 Fuzzy sets (T1-FS) Type-2 Fuzzy sets (T2-FS) Fuzzy Logic System (FLS) Interval Type-II Fuzzy Logic Systems (IT2-FLS)

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