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针对煤矿井下工作面瓦斯浓度预测存在的不足,结合混沌时间序列可预测的特点,基于混沌理论重构了瓦斯浓度时间序列的相空间,确定了该相空间的时间延迟和嵌入维数,并在相空间中,利用加权1阶局域法建立了工作面瓦斯浓度预测模型,并结合某煤矿工作面瓦斯浓度实测数据进行了瓦斯浓度预测研究。研究结果表明:该煤矿工作面瓦斯浓度预测结果与实际情况较吻合,该预测模型具有较高的精度。
Aiming at the shortcoming of gas concentration prediction in coal mine working face and combining with the predictable characteristics of chaotic time series, the phase space of gas concentration time series is reconstructed based on chaos theory. The time delay and embedding dimension of gas phase concentration are determined. In the phase space, the prediction model of gas concentration in working face was established by weighted first order local method. The gas concentration prediction was studied based on the measured data of gas concentration in a coal mine working face. The results show that the prediction results of gas concentration in coal mine face are in good agreement with the actual situation, and the prediction model has high accuracy.