A new improved forecasting method integrated fuzzy time series with the exponential smoothing method. (1st January 2013)

• Record Type: Journal Article
• Authors: Ge, Peng; Wang, Jun; Ren, Peiyu; Gao, Huafeng; Luo, Yuyan
• Is Part Of: International journal of environment and pollution. Volume 51:Number 3/4(2013)
• Page Start: 206
• Page End: 221
• Publication Date: 2013-01-01
• Subjects: forecasting -- fuzzy time series -- fuzzy logical relations -- exponential smoothing method; Environmental policy -- Periodicals; Environmental engineering -- Periodicals; Environmental sciences -- Periodicals; Pollution -- Periodicals; 363.73
• Languages: English
• ISSNs: 0957-4352

Abstract

This paper presents a new method of integrated fuzzy time series with the exponential smoothing method to forecast university enrolments. The data of historical enrolments of the University of Alabama shown in Liu et al. (2011) are adopted to illustrate the forecasting process of the proposed method. A comparison has been made with five previous fuzzy time series models. Meanwhile, the mean squared error has also been calculated as the evaluation criterion to illustrate the performance of the proposed method. The empirical analysis shows that the proposed model reflects the fluctuations in fuzzy time series better and provides better overall forecasting results than the five listed previous models.