Mine water inflow prediction based on superimposed Markov chain

Superimposed Markov chain was proposed to predict mine water inflow quantitatively since the general Markov chain has limitations. . Based on the water inflow data in the Chengzhuang coal mine from January 2008 to December 2013( 72 months) , water inflow status was classified, state transition matrix was calculated, the predicted values from different step ma 2 trixes were superimposed and averaged, and thus the superimposed Markov chain model was built and the fitting results were analyzed. The water inflow data from January to April 2014 were predicted and compared with the observed data. The results showed that the model prediction accuracy is about 94. 84%, so this new method can be used for mine water inflow prediction.

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