Research Article
ARIMA based Interval Type-2 Fuzzy Model for Forecasting
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 28 - Issue 3 |
| Published: August 2011 |
| Authors: Saima H., J. Jaafar, S. Belhaouari, T.A. Jillani |
10.5120/3369-4652
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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 },
year = { 2011 },
volume = { 28 },
number = { 3 },
pages = { 17-21 },
doi = { 10.5120/3369-4652 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A Saima H.
%A J. Jaafar
%A S. Belhaouari
%A T.A. Jillani
%T ARIMA based Interval Type-2 Fuzzy Model for Forecasting%T
%J International Journal of Computer Applications
%V 28
%N 3
%P 17-21
%R 10.5120/3369-4652
%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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