The Set SFmBDR of Fuzzy Time Series Forecasting Models
- 10.2991/msam-17.2017.12How to use a DOI?
- forecasting method of fuzzy time series; fuzzy function of SFmBDR;Inverse fuzzy function of SFmBDR; forecasting function of SFmBDR
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.
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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 - Proceedings of the 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 - 10.2991/msam-17.2017.12 ID - Feng2017/03 ER -