Research on Time Series of Gas Trend Based on R Language

Abstract

Abstract-Use the history monitoring data of the gas of Shaanxi Huangling No.2 coal mine, the time series of monitoring data are decomposed and smoothed by using R language. The abnormal and missing values in the raw data are analyzed and three methods of time series smoothing (Simple exponential smoothing method, Holt exponential smoothing method and Holt-Winters exponential smoothing method) are used to predict the variation law of gas concentration. The actual value and the predicted value are compared to verify the effectiveness of the forecasting method, and the conclusion can make practical significance for the safe production of the mine.