The Set SFmBDR of Fuzzy Time Series Forecasting Models

DOI

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

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  -