矿井涌水量的中长期混沌预测

A long-period chaotic prediction model of mine discharge

针对目前采煤矿井涌水量预测模型误差较大的问题,利用混沌理论对矿井涌水量进行混沌特征辨识,在此基础上,建立矿井涌水量中长期混沌预测模型。以平煤十二矿为例,对矿井涌水量序列(时间尺度为月)进行分析,其中最大Lyapunov指数为0.161 1,大于0,说明该序列具有混沌特征。计算了时间延迟(τ=12月)和嵌入维数(m=9),对涌水量序列进行相空间重构,建立了矿井涌水量中长期混沌预测模型(预测周期为6个月)。与实测结果对比,模型的预测精度达到了99.37%。该预测模型为矿山多季度安全生产计划的制定及水害防治提供了科学依据。

In view of forecast model of the current coal mine discharge having the larger error, the authors car- ried out chaotic identification for mine discharge using chaotic theory, and set up a mid-long-period chaotic prediction for the mine discharge. Took Pingdingshan No. 12 Coal Mine as an example,mine discharge series was studied. The max Lyapunov exponent A was 0. 161 1 ,indicating that the sequence has chaotic characteris- tics. The time delay τ （τ= 12 months） and embedding dimension m （m = 9）, were calculated, respectively. The phase-space reconstruction of mine discharge was established, and the medium and long-term chaotic prediction model for the mine discharge was also （ the prediction period 6 months）. Contrasted with the measured results, the accuracy of the prediction model had reached about 99.37%. So, the prediction model provides scientific basis for the development of mine multi-quarter safe production planning and mine disaster control.