Prediction of Gas Concentration Based on ARIMA and GARCH Model

DOI

10.2991/seeie-19.2019.16How to use a DOI?

Keywords

gas emission concentration; time series; ARIMA model; GARCH model; prediction; fitting; R language

Abstract

In order to accurately predict the dynamic gushing process of gas in fully mechanized mining face, based on the historical monitoring data of underground gas concentration, with the help of R language, the ARIMA model is first established and fitted to determine the prediction equation of the ARIMA (p, d, q). The results of data fitting show that the model has a high degree of fitting to the gas concentration time series. Then the GARCH (u, v) is applied to the residual sequence of ARIMA (p, d, q), and the predicted value of the noise term in the ARIMA model is simulated, and the prediction result of the gas emission concentration is optimized. Finally, the 1001 fully mechanized mining face of Huangling No. 1 Mine in Shaanxi Province is taken as an application example. The results show that the combined model of ARIMA (p, d, q) and GARCH (u, v) can not only reflect the change trend of gas emission concentration but also has a high fitting effect and prediction accuracy.

Copyright

© 2019, 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  - Lizhi Zhang
AU  - Zaihua Yang
PY  - 2019/05
DA  - 2019/05
TI  - Prediction of Gas Concentration Based on ARIMA and GARCH Model
BT  - Proceedings of the 2019 2nd International Conference on Sustainable Energy, Environment and Information Engineering (SEEIE 2019)
PB  - Atlantis Press
SP  - 70
EP  - 74
SN  - 2352-5401
UR  - https://doi.org/10.2991/seeie-19.2019.16
DO  - 10.2991/seeie-19.2019.16
ID  - Zhang2019/05
ER  -