Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)

The Set of Fuzzy Time Series Forecasting Models Based on the Ordered Difference Rate

Authors
Chengguo Yin, Hongxu Wang, Hao Feng, Xiaoli Lu
Corresponding Author
Chengguo Yin
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.9How to use a DOI?
Keywords
fuzzy time series forecasting method; fuzzy number function of SFBODR; inverse fuzzy number function of SFBODR; forecasting function of SFBODR
Abstract
Song and Chissom established fuzzy time series forecasting model in 1993. Stevenson and Porter improved the forecasting model of Jilani, Burney, and Ardil in 2009, and researched the forecasting problem of enrollments of the University of Alabama 1971–1992. Although they obtained the best prediction accuracy by 2009, the prediction accuracy was still not ideal. In this paper, we improved the forecasting model of Stevenson and Porter, and got the SFBODR (The Set of Fuzzy Time Series Forecasting Models Based on the Ordered Difference Rate). The forecasting model SFBODR(0.00004, 0.00003) can get the ideal state of AFER(Average Forecasting Error Rate) = 0% and MSE(Mean Square Error) = 0 in forecasting the enrollments of the University of Alabama.
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Proceedings
2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2017
ISBN
978-94-6252-324-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/msam-17.2017.9How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chengguo Yin
AU  - Hongxu Wang
AU  - Hao Feng
AU  - Xiaoli Lu
PY  - 2017/03
DA  - 2017/03
TI  - The Set of Fuzzy Time Series Forecasting Models Based on the Ordered Difference Rate
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 34
EP  - 37
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.9
DO  - https://doi.org/10.2991/msam-17.2017.9
ID  - Yin2017/03
ER  -