Hidden Markov Model for Predicting the Turning Points of GDP Fluctuation

DOI

10.2991/icfcce-14.2014.1How to use a DOI?

Keywords

GDP, turning point, hidden Markov model, dynamic Bayesian network

Abstract

At present, the methods of predicting the turning points of GDP fluctuation is difficult to choose suitable influence indexes, and emphasize static function dependency or dynamic propagation of time series so that the static and dynamic information can not be consistently combined. In this paper, hidden Markov model is introduced for predicting the turning points of GDP fluctuation. The real GDP data of China from 1990 to 2013 is used for modeling and the experimental results show that hidden Markov model has good practicability and reliability.

Copyright

© 2014, 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  - Cuiping Leng
AU  - Shuangcheng Wang
PY  - 2014/03
DA  - 2014/03
TI  - Hidden Markov Model for Predicting the Turning Points of GDP Fluctuation
BT  - Proceedings of the 2014 International Conference on Future Computer and Communication Engineering
PB  - Atlantis Press
SP  - 1
EP  - 3
SN  - 1951-6851
UR  - https://doi.org/10.2991/icfcce-14.2014.1
DO  - 10.2991/icfcce-14.2014.1
ID  - Leng2014/03
ER  -