Comparison of pattern matching Fuzzy Models and Box- Jenkins models  To predict suscriptions case : Mobilis   (2009-2012)

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DC Field	Value	Language
dc.contributor.author	جمال دقيش	-
dc.contributor.author	مصطفى خربوش	-
dc.date.accessioned	2017	-
dc.date.available	2017	-
dc.date.issued	2017	-
dc.identifier.issn	2437-1033	-
dc.identifier.uri	http://dspace.univ-ouargla.dz/jspui/handle/123456789/16099	-
dc.description	Journal of Quantitative Economics Studies JQES	en_US
dc.description.abstract	This study is designed to forecast Subscriptions service prepaid in Mobilis, by approach of Box-Jenkins and pattern matching Fuzzy Models and to choose the best model of family models ARIMA. The research found that the model box-Jenkins has achieved the highest forecast accuracy by comparing pattern matching Fuzzy Models, and the time series of subscriptions for the service prepaid in Mobilis is non-stationary, and to make it stationary the first differences are applied. The best model among the models that have been developed in this study for forecasting the number of subscriptions is an ARIMA model (2.1.0).	en_US
dc.language.iso	other	en_US
dc.relation.ispartofseries	Number 03 2017;	-
dc.subject	Forecast	en_US
dc.subject	Times Series Analysis	en_US
dc.subject	Pattern Matching Fuzzy	en_US
dc.subject	Box-Jenkins	en_US
dc.subject	Stationary and ARIMA	en_US
dc.title	Comparison of pattern matching Fuzzy Models and Box- Jenkins models To predict suscriptions case : Mobilis (2009-2012)	en_US
dc.type	Article	en_US
Appears in Collections:	Number 03 /2017

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