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

The Set SFmBDR of Fuzzy Time Series Forecasting Models

Authors
Hao Feng, Hongxu Wang, Chengguo Yin, Xiaoli Lu
Corresponding Author
Hao Feng
Available Online March 2017.
DOI
https://doi.org/10.2991/msam-17.2017.12How to use a DOI?
Keywords
forecasting method of fuzzy time series; fuzzy function of SFmBDR;Inverse fuzzy function of SFmBDR; forecasting function of SFmBDR
Abstract
Fuzzy time series forecasting models are created by Song and Chissom in 1993. In 2012, Saxena, Sharma& Easo put forward the forecasting model which more improve the forecasting accuracy. According to this, this paper improve the set SFmBDR of fuzzy time series forecasting model based on differential rate. The forecasting model SFmBDR (0.000002,0.000004) and SFmBDR (0.000004,0.000002) of SFmBDR can gain the AFER=0% and MSE=0, during we study the problems of enrollments data of University of Alabama in 1971~1992. They should have better application potential.
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-17.2017.12How 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  - Hao Feng
AU  - Hongxu Wang
AU  - Chengguo Yin
AU  - Xiaoli Lu
PY  - 2017/03
DA  - 2017/03
TI  - The Set SFmBDR of Fuzzy Time Series Forecasting Models
BT  - 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
PB  - Atlantis Press
SP  - 45
EP  - 48
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-17.2017.12
DO  - https://doi.org/10.2991/msam-17.2017.12
ID  - Feng2017/03
ER  -