A hybrid forecast model combining fuzzy time series, linear regression and a new smoothing technique
- DOI
- 10.2991/ifsa-eusflat-15.2015.192How to use a DOI?
- Keywords
- Fuzzy time series, linear regression, smooth-ing technique, forecasting.
- Abstract
In recent years, Fuzzy Time Series have been considered a promising tool to deal with forecasting problems due to the ease to model the problems, the satisfactory results obtained and also to the low computational cost required. However, the long experience with traditional methods coming from statistics, certainly brings a rich knowledge that can be used to enhance the computational methods employed to deal with Fuzzy Time Series. This paper in-troduces a forecast model where Fuzzy Time Series, lin-ear regression and a new smoothing method are com-bined. Experiments were performed with the Taiwan Stock Exchange index and compared with eight others approaches found in the literature. The results confirm that the proposed model presents a good accuracy with relation to the other methods.
- Copyright
- © 2015, 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/).
Cite this article
TY - CONF AU - Fábio José Justo dos Santos AU - Heloisa De Arruda Camargo PY - 2015/06 DA - 2015/06 TI - A hybrid forecast model combining fuzzy time series, linear regression and a new smoothing technique BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1362 EP - 1368 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.192 DO - 10.2991/ifsa-eusflat-15.2015.192 ID - JustodosSantos2015/06 ER -