Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology

An Enhanced HMM-Based for Fuzzy Time Series Forecasting Model

Authors
Yi-Chung Cheng, Pei-Chih Chen, Chih-Chuan Chen, Hui-Chi Chuang, Sheng-Tun Li
Corresponding Author
Yi-Chung Cheng
Available Online June 2015.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

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  - 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.47
DO  - https://doi.org/10.2991/ifsa-eusflat-15.2015.47
ID  - Cheng2015/06
ER  -