Institute of Resources & Environment,Henan Polytechnic University
Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization,Henan Polytechnic University
Henan Energy and Chemical Industry Group Research Institute Co.,Ltd.

为提高矿井涌水量预测精度,以洛阳龙门矿为例,基于2011年1月—2020年12月正常涌水量序列,提出灰色-多步马尔科夫模型,并用2021年1—4月实测正常涌水量验证模型。结果表明:灰色-多步马尔科夫模型预测精度达99.35%,明显高于单一灰色GM(1,1)模型和灰色-马尔科夫模型;灰色-多步马尔科夫模型对波动较大的非平稳序列拟合效果良好,可在一定程度上减少预测主观性,预测精度较高,是进行矿井涌水量预测的一种有效方法。

To improve the prediction accuracy of mine water inflow,taking Longmen Mine in Luoyang as an example,a grey multi-step Markov model was proposed based on the normal water inflow sequence from January 2011 to December 2020. And the model was validated by using the measured water inflow from January to April 2021.The results showed that the prediction accuracy of the gray multi-step Markov model reached 99.35%,which was significantly higher than the prediction accuracy of a single gray model and gray-Markov model.The greymulti-step Markov model had a good fitting effect on non-stationary series with large fluctuations,reduced certain subjectivity and improved predict accuracy,which could provide an effec‑tive method for mine water inflow prediction.

国家自然科学基金资助项目（41972254）；河南省高校重点科研项目（22A170009）；

0 引言
1 研究区概况和数据来源
2 预测模型的构建
2.1 灰色-多步马尔科夫模型基本思路
2.2 预测具体步骤
3 预测结果
4 讨论
4.1 与单一灰色模型比较
4.2 与灰色-马尔科夫模型比较
4.3 马尔科夫模型的无后效性
4.4 矿井水文地质类型
5 结论

李建林,王路扬,李松营等.基于灰色-多步马尔科夫模型的矿井涌水量预测[J].河南理工大学学报(自然科学版),2023,42(05):66-71.DOI:10.16186/j.cnki.1673-9787.2021060039.