等维新息灰色马尔科夫在矿井涌水量预测中的应用

矿井涌水量准确预测对于煤矿安全生产具有重要意义。为了进一步提高矿井涌水量预测精度，针对矿井涌水量可用数据少且存在未知影响因素，在灰色马尔科夫预测模型的基础上引入等维新息思想，构建等维新息灰色马尔科夫预测模型。通过分析高河煤矿2008—2017年矿井涌水量原始数据，预测2018和2019年矿井涌水量数据，并对3种预测方法的预测精度进行对比分析。研究结果表明：等维新息马尔科夫预测模型符合矿井涌出量数据特征，引入等维新息思想能够避免旧数据贡献值低的问题，预测精度得到进一步提高；等维新息马尔科夫预测模型的预测精度比灰色理论、马尔科夫预测模型的预测精度平均高3.11%和0.22%,预测值与实际矿井涌水量更加接近，具有较好的适应性。

Application of Equal-dimensional and New-information Grey Markov in Mine Water Inflow Prediction

Accurate prediction of mine water inflow is of great significance to mine safety production. In order to further improve the prediction accuracy of mine water inflow, considering that the available data of mine water inflow are few and there are unknown influencing factors, the idea of equal dimension new information is introduced on the basis of the grey Markov prediction model, and the grey Markov prediction model of equal dimension new information is built. By analyzing the original data of mine water inflow in Gaohe Coal mine from 2008 to 2017, the data of mine water inflow in 2018 and 2019 are predicted, and the prediction accuracy of the three prediction methods is compared and analyzed. The results show that the equal-dimension new information Markov prediction model accords with the characteristics of mine gusher data, and the introduction of equal-dimension new information can avoid the problem of low contribution value of old data, and the prediction accuracy can be further improved. Compared with the average accuracy of grey theory and Markov prediction model, the prediction accuracy of isodimension Xinshi Markov prediction model is 3.11% and 0.22% higher. The predicted value is closer to the actual mine water inflow, which has good adaptability.