A computational method based on interval length for fuzzy time series forecasting

dc.authorid0000-0002-9539-7202en_US
dc.contributor.authorAkay, Özlem
dc.date.accessioned2022-04-20T09:50:01Z
dc.date.available2022-04-20T09:50:01Z
dc.date.issued2021en_US
dc.departmentMTÖ Üniversitesien_US
dc.description.abstractIn the literature, there have been a good many different forecasting methods related to forecasting problems of fuzzy time series. The main issue of fuzzy time series forecasting is the accuracy of the forecasted values. The forecasting accuracy rate is affected by the length of each interval in the universe of discourse. Thus, it is substantial to determine the length of each interval. In this study, a new computational method based on class width to determine interval length is proposed and also used the coefficient of variation for time series forecasting. After the intervals are formed, the historical time series data set is fuzzified according to fuzzy time series theory. The proposed model has been tested on the student enrollments, University of Alabama, and a real-life problem of rice production for containing higher uncertainty. This method was compared with existent methods to determine the effectiveness in terms of the mean square error (MSE) and the average forecasting (AFE). The results are shown that the proposed model can achieve a higher forecasting accuracy rate than the existing models.en_US
dc.identifier.citationAkay, Ö. (2021). A computational method based on interval length for fuzzy time series forecasting . NATURENGS , 2 (1) , 22-33en_US
dc.identifier.doi10.46572/naturengs.882203
dc.identifier.endpage33en_US
dc.identifier.issn2717-8013en_US
dc.identifier.issue1en_US
dc.identifier.startpage22en_US
dc.identifier.urihttps://dergipark.org.tr/tr/pub/naturengs
dc.identifier.urihttps://hdl.handle.net/20.500.12899/1019
dc.identifier.volume2en_US
dc.language.isoenen_US
dc.relation.ispartofNATURENGSen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Başka Kurum Yazarıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectInterval Lengthen_US
dc.subjectCoefficient of Variationen_US
dc.subjectFuzzifieden_US
dc.subjectFuzzy Time Seriesen_US
dc.subjectForecastingen_US
dc.titleA computational method based on interval length for fuzzy time series forecastingen_US
dc.typeArticleen_US

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