Study of Gas Emission Quantity Prediction Based on Chaotic Time Series

Abstract

The gas is one of the most important factors that endanger the security of the mine production. At present, the mine has only realized the real-time monitoring of gas, but not the forcasting of gas.There are some limitation of the traditional forcasting method, such as modeling subjectivism and statistical forcasting. This paper presents the gas emission forecasted method by using chaos time series forecasting,and on this basis to establish time-series forecasting models. The results show that the gas emission system has the chaotic property, using chaotic time series forecasting method to forecast the amount of gas emission is feasible, and the prediction accuracy is improved after improving some parameters algorithms in the chaotic time series prediction algorithm. The contents of this article has laid a theoretical basis for non-contact coal and gas outburst dynamic forecast, but also open up new ideas for in-depth analysis of the gas emission complex.