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ARIMA based Interval Type-2 Fuzzy Model for Forecasting

International Journal of Computer Applications
© 2011 by IJCA Journal
Number 3 - Article 3
Year of Publication: 2011
Saima H.
J. Jaafar
S. Belhaouari
T.A. Jillani

Saima H., J Jaafar, S Belhaouari and T A Jillani. Article: ARIMA based Interval Type-2 Fuzzy Model for Forecasting. International Journal of Computer Applications 28(3):17-21, August 2011. Full text available. BibTeX

	author = {Saima H. and J. Jaafar and S. Belhaouari and T.A. Jillani},
	title = {Article: ARIMA based Interval Type-2 Fuzzy Model for Forecasting},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {28},
	number = {3},
	pages = {17-21},
	month = {August},
	note = {Full text available}


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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