基于灰色马尔可夫模型的采煤机生产率的预测

生产率是衡量采煤机工作性能的一项重要指标，对煤矿开采的科学决策以及发展规划具有重要的指导意义.通过建立采煤机生产率的指标评价体系，运用灰色GM (1,1)模型以及灰色马尔可夫模型分别进行了预测，经过比较可发现，灰色马尔可夫模型预测的准确率和预测精度都优于GM(1,1)模型，尤其对波动性和随机性大的数据具有很好的拟合和预测效果，为具有多因素影响的采煤机生产性能预测评价提供了一种有效的途径和方法.

The forecast of shearer productivity based on gray Markov model

Productivity is a measure of an important indicator of the shearer performance， which is of important guiding significance for the scientific decision－making and development of coal mining plan. In this paper， index evaluation system of the shearer productivity is established， and forecast to the shearer productivity is carried using grey GM (1， 1) model and grey Markov model separately. After comparison it is found that the grey Markov model prediction accuracy and precision are better than GM (1， 1) model， especially for data with large volatility and randomness which has the very good fitting and prediction effect. The grey Markov model provides an effective way and method for the prediction assessment of shearer production performance influenced by multiple factors.