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针对煤矿井下瓦斯涌出量的特殊影响因素和灰色系统建模的特点,以煤矿瓦斯动态监测数据为基础,通过灰色系统建模、关联度分析及残差辨识,建立了灰色系统新陈代谢动态模型,并将该模型应用到某矿瓦斯涌出量预测分析中,由事中及事后检验结果可知:原始数据一次累加后进行的GM(1,1)预测中,新陈代谢动态模型预测矿井瓦斯涌出量的拟合精度高,结果准确可靠,克服了一般模型对井下瓦斯涌出量数据采集、模型建立的困难,实现了瓦斯涌出量的动态预测,可为煤矿安全管理的正确决策提供科学依据.
According to the special factors of gas emission and the characteristics of gray system modeling in coal mine, based on the dynamic monitoring data of coal mine, the dynamic model of gray system was established through gray system modeling, correlation analysis and residual identification. The model is applied to the prediction and analysis of the gas emission of a mine. From the facts and ex post facto tests, it can be seen that in the GM (1,1) prediction after the accumulation of the primary data, the metabolic dynamic model predicts the gas emission from the mine The method has the advantages of high fitting accuracy and accurate and reliable results, overcomes the difficulty of data collection and model establishment of general gas emission system and realizes the dynamic prediction of gas emission amount, and can provide scientific basis for correct decision of coal mine safety management.