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Shearer height adjusting is a key technology for shearer automation. Considering constraints of present shearer height adjusting,this paper built grey-markovian memory cutting algorithm after analyzing traditional shearer memory cutting algorithm. We firstlyconstructed prediction mechanism using grey model, then determined state transition probability matrix using markovian, so as to revisefeedback of grey model and achieve automatic height adjusting. Finally we simulated this model to get reliability. By comparing greymarkovianmemory cutting algorithm with traditional memory cutting algorithm, it is concluded that the grey-markovian model hashigher efficiency and accuracy