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/).

Download article (PDF)

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  -