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 |
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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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