An Enhanced HMM-Based for Fuzzy Time Series Forecasting Model

Autor: Yi-Chung Cheng, Hui-Chi Chuang, Pei-Chih Chen, Chih-Chuan Chen, Sheng-Tun Li
Rok vydání: 2015
Předmět:
Zdroj: IFSA-EUSFLAT
ISSN: 1951-6851
DOI: 10.2991/ifsa-eusflat-15.2015.47
Popis: The fast and accurate forecasting method can help makers to make appropriate strategy. Zadeh was given the definition 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 considers 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.
Databáze: OpenAIRE