基于Hurst指数的矿井涌水量定量预测

    Quantitative Prediction of Mine Inflow Based on Hurst Exponent

    • 摘要: 在Hurst指数趋势分析的基础上,考虑时间序列长度、相关性等因素,并结合计算机语言,实现了R/S方法的定量预测,成功的将非线性时间序列预测方法从定性走向定量。以赵家寨煤矿矿井涌水量为例,分别对突水前和突水后的涌水量时间序列进行了R/S定量预测,模型预测精确度高达92.48%和94.75%,表明该模型精确度高、适用性强。

       

      Abstract: Based on analyzing the trend of Hurst exponent and considering the length of time series, as well as the relation among inflow water data in mines, a quantitative prediction of R/S method from qualitative to quantitative of nonlinear time series has been obtained by computer successfully. Taking the inflow water in Zhaojiazhai Mine as the example, the time series of inflow water, before and after water inrush, have been carried out by the quantitative prediction of R/S method. The prediction accuracy is as high as 92.48% and 94.75% respectively. It shows that the model has high-precision and strong applicability.

       

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