基于等维GM(1,1)-马尔可夫链模型的涌水量预测研究

Mine Infow Forecast Based on the Equivalent Novelty Grey Markov

准确预测涌水量对于煤矿安全生产具有重要意义,采用等维新息灰色GM(1,1)预测模型和改进的马尔可夫模型相结合的方式建立了等维新息灰色马尔科夫预测模型.首先采用该模型对样本数据进行了灰色预测,并根据真实数据与预测结果之间的误差划分状态区间,并且建立转移概率矩阵,利用转移矩阵和误差百分比状态计算得出改进的马尔可夫修正值,并对预测结果进行修正,实现了涌水量波动性预测,预测结果表明,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;等维新息灰色马尔科夫预测模型的预测精度最高,较灰色理论和灰色马尔科夫模型分别提高了0.4194%、2.5649%.

Accurate prediction of water inflow is of great significance for coal mine safety production.The prediction model is established by combining the gray GM(1,1)prediction model and the improved Markov model.The model was first used to predict the grey color on the sample data,And divide the state interval according to the error between the real data and the prediction results,And build a transition probability matrix,Improved Markov modified values were calculated using the transfer matrix and the error percentage state,And to correct the prediction results,Realize the prediction of water inflow volatility,The prediction results showed that,The new Markov prediction model meets the characteristics of mine emission data,The introduction of new interest ideas can avoid the problem of low contribution value of old data,The prediction accuracy has been further improved;The Io grey Markov prediction model has the highest prediction accuracy,The relatively grey theory and the grey Markov model are improved by 0.4194%and 2.5649%,respectively.