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

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

Authors
Xiaojing Zhu, Hongxu Wang, Chengguo Yin, Xiaoli Lu
Corresponding Author
Xiaojing Zhu
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.13How to use a DOI?
Keywords
fuzzy time series forecasting method; SFBDR fuzzy number function; SFBDR inverse fuzzy number function; SFBDR Predicted function
Abstract
Song & Chissom introduced the concept of fuzzy time series in 1993[1], and many fuzzy time series methods have been proposed, however, the prediction accuracy is not high, among which, Jilani, Burney and Ardil (2007) proposed prediction model has achieved a high accuracy. This paper improves their predicted model, and proposed the set of fuzzy time series forecasting models Based on the difference rate, simplified as SFBDR, it contains the predicted model SFBDR (0.000001, 0.000003) and SFBDR (0.000003, 0.000001), in the historical enrollment of University of Alabama it can get the highest predicted accuracy of AFER=0% and MSE=0.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

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-17.2017.13How 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  - Xiaojing Zhu
AU  - Hongxu Wang
AU  - Chengguo Yin
AU  - Xiaoli Lu
PY  - 2017/03
DA  - 2017/03
TI  - Set of Fuzzy Time Series Forecasting Models Based on the Difference Rate
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 49
EP  - 52
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.13
DO  - https://doi.org/10.2991/msam-17.2017.13
ID  - Zhu2017/03
ER  -