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A Hybrid Fuzzy Time Series Model for Forecasting

Saima, H and Jaafar, J. and Brahim Belhaouari, Samir (2012) A Hybrid Fuzzy Time Series Model for Forecasting. Engineering Letters, 20 (1). pp. 88-93. ISSN 1816-094

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Abstract

Researchers are finding their way to solve the chaotic and uncertain problems using 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 an integrated fuzzy time series model based on ARIMA and IT2-FLS is presented. The propose model will use ARIMA to select appropriate coefficients from the observed dataset. IT2-FLS is utilized here for forecasting the result with more accuracy and certainty.

Item Type:Article
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:7487
Deposited By: Dr Jafreezal Jaafar
Deposited On:12 Mar 2012 00:14
Last Modified:19 Jan 2017 08:21

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