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ARIMA based Interval Type-2 Fuzzy Model for Forecasting

H., Saima and Jaafar, J. and Samir, B. B. and Jillani, T.A. (2011) ARIMA based Interval Type-2 Fuzzy Model for Forecasting. [Citation Index Journal]

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Official URL: http://www.ijcaonline.org/archives/volume28/number...

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.

Item Type:Citation Index Journal
Impact Factor:Published by Foundation of Computer Science, New York, USA
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:6418
Deposited By: Dr Jafreezal Jaafar
Deposited On:26 Sep 2011 09:36
Last Modified:19 Jan 2017 08:22

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