液压支架支护效果评价的动态分析

Dynamic Analysis of the Evaluation of Hydraulic Support Effectiveness

针对智能化开采过程中无法准确评定液压支架支护效果的问题,借助改进后的卷积神经网络并通过时空维度建立七种动态评价标准进行研究分析。研究发现改进后的神经网络在依靠七种动态评价标准的条件下,评价准确性和速率能够提升15%左右,表明建立的评价方法在智能化采矿中有一定优势,为强化液压支架在智能化开采中的应用提供了参考价值。

Aiming at the problem of inaccurate evaluation of hydraulic support effectiveness in the intelligent mining process,an improved convolutional neural network is used to establish seven dynamic evaluation standards through spatiotemporal dimensions for research and analysis.The research found that the improved neural network can improve the accuracy and speed of evaluation by about 15%under the conditions of relying on seven dynamic evaluation standards,indicating that the established evaluation method has certain advantages in intelligent mining and provides reference value for strengthening the application of hydraulic supports in intelligent mining.