时间序列模型在工作面涌水量预测中的应用

在矿山实际生产过程中,涌水量预测对于矿山防治水具有重要意义。以山东郓城煤矿1301工作面为研究对象,先不考虑季节性因素影响的条件下,采用时间序列分析模型ARIMA建立涌水量与时间的函数关系,迭代拟合结果精度低,表明郓城煤矿1301工作面涌水量时间序列受季节性因素影响;在此基础上,基于时间序列加法分解原理,分离提取涌水量时间序列中的长期趋势、季节指数、循环因子和随机变动参数,并应用熵权法确定各参数权重,建立工作面涌水量预测的非线性回归修正模型,并将模拟预测结果与忽略季节效应的ARIMA模型预测的涌水量进行对比,结果表明,建立的非线性时间序列模型计算的涌水量更为接近实测涌水量,验证了方法的准确性。研究成果将为矿井涌水量预测提供新思路。

Application of time series model in water inflow prediction of working face

In practical production of mines, the prediction of mine water inflow is of great significance for mine water prevention and control. Taking working face 1301 of Yuncheng coal mine as the research object, and without considering the influence of seasonal factors, ARIMA-the time series analysis model-is used to establish the functional relationship between mine water inflow and time, which proves that the time series of water inflow in working face 1301 of Yuncheng coal mine is affected by seasonal factors. Then, based on the principle of addition and decomposition of time series, the long-term trend, seasonal indexes, circulating factors and random parameters in the water inflow time series are separated and extracted, and the nonlinear regression correction model of water inflow prediction is established through applying the entropy method to determine the weight of each parameter. After that, the simulation results are compared with the water inflow by using ARIMA model ignoring the seasonal effect. The results show that the prediction of mine water inflow based on the non-linear time series of entropy weight is close to the measured water inflow, which verifies the accuracy of the method.