A new approach based on the optimization of the length of intervals in fuzzy time series
Küçük Resim Yok
Tarih
2011
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IOS PRESS
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In fuzzy time series analysis, the determination of the interval length is an important issue. In many researches recently done, the length of intervals has been intuitively determined. In order to efficiently determine the length of intervals, two approaches which are based on the average and the distribution have been proposed by Huarng [4]. In this paper, we propose a new method based on the use of a single variable constrained optimization to determine the length of interval. In order to determine optimum length of interval for the best forecasting accuracy, we used aMATLAB function which is employing an algorithm based on golden section search and parabolic interpolation. Mean square error is used as a measure of forecasting accuracy so the objective function value is mean square error value for forecasted observations. The proposed method was employed to forecast the enrollments of the University of Alabama to show the considerable outperforming results.
Açıklama
Anahtar Kelimeler
Forecasting, fuzzy sets, fuzzy time series, length of interval, optimization
Kaynak
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
22
Sayı
1
