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为真实还原矿井涌水动态特征,开展了基于相空间重构理论的矿井涌水量混沌预测研究。采集某铅锌矿山日涌水量时间序列,运用互信息函数法和Cao氏方法确定重构参数,以此对原始序列展开相空间重构。根据对重构序列主分量谱图及最大Lyapunov指数的分析,确定了重构序列的混沌特征,并计算其有效预测时长为13d,在有效预测时长内,平均预测误差为4.81%,预测效果较好;超过有效预测时长后,预测精度迅速下降,平均预测误差为15.13%。结果表明,将混沌方法用于矿井涌水量预测具有原理简单、计算效率高等优点,但仅适用于短期预测。
In order to reduce the dynamic characteristics of mine gushing water, a chaotic forecasting method based on phase space reconstruction theory is proposed. The time series of inrush water volume of a lead-zinc mine was collected, and the reconstruction parameters were determined by mutual information function method and Cao’s method, so as to reconstruct the original sequence phase space. Based on the analysis of the principal component spectrum and the largest Lyapunov exponent of the reconstructed sequence, the chaotic characteristics of the reconstructed sequence were determined. The effective prediction time was 13d, and the average prediction error was 4.81% within the effective prediction time. Good; Exceed the effective prediction time, the prediction accuracy decreased rapidly with the average prediction error of 15.13%. The results show that the chaos method used in mine water inflow prediction has the advantages of simple principle and high computational efficiency, but only for short-term prediction.