An ARMA Prediction Model for Electromagnetic Radiation Data Preceeding a Rock Burst
LIU Zhen-tang
LIU Xiao-fei
WANG En-yuan
Abstract：SAS statistical analysis software was used to test the randomness of electromagnetic radiation (EMR) observed during the "1.12 rock burst" of the number 237 working face in the Nanshan coal mine. An auto-regressive-moving-average (ARMA) model was fitted to the EMR data and used to forecast twelve observations into the future. The results show that the rock burst EMR data are non-white noise, stationary and can be fitted with an AR(3) model. Com-paring the model EMR values to the real data, the similarity degree is about 66%. An ARMA model can use data preceding an event to describe changes in the EMR trends quantitatively.
Keywords：rock burstelectromagnetic radiation (EMR)time seriesprecursorARMA model
Publication Date：2009-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 316-320 )