An Enhanced HMM-Based for Fuzzy Time Series Forecasting Model

DOI

10.2991/ifsa-eusflat-15.2015.47How to use a DOI?

Keywords

Fuzzy time series, forecasting, hidden Mar-kov model (HMM)

Abstract

The fast and accurate forecasting thod can help mak-ers to make appropriate strategy. Zadeh was given the efinition of a fuzzy set in 1965. Song and Chissom proposed the definition and the forecasting framework of fuzzy time series in 1993. Sullivan and Woodall first proposed the forecasting method to handle one factor with probability Markov model in 1994. Li and Cheng proposed a stochastic hidden Markov model which con-siders two factors in 2010. However, an event can be affected by many factors. In this paper, we present a multi-factor HMM-based forecasting, and utilize more factors to get better forecasting accuracy rate.

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/).

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TY  - CONF
AU  - Yi-Chung Cheng
AU  - Pei-Chih Chen
AU  - Chih-Chuan Chen
AU  - Hui-Chi Chuang
AU  - Sheng-Tun Li
PY  - 2015/06
DA  - 2015/06
TI  - An Enhanced HMM-Based for Fuzzy Time Series Forecasting Model
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  - 320
EP  - 325
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.47
DO  - 10.2991/ifsa-eusflat-15.2015.47
ID  - Cheng2015/06
ER  -