基于人工神经网络薄煤层采煤方法优选专家系统研究

    Research on the Optimization selection of thin coal seam mining method based on ANNES

    • 摘要: 薄煤层安全高效开采是我国煤炭开采迫切需要解决的问题,而优选薄煤层采煤方法更显的尤为重要,薄煤层采煤方法的选择不仅受到地质条件的限制,而且还受到煤矿的设备水平和人为因素的影响。本文针对薄煤层采煤的特点,建立了薄煤层采煤方法选择人工神经网络专家系统,本系统中利用神经网络的改进算法"自适应学习法"训练网络,最终预测出采煤方法和工作面技术经济指标(工作面单产以及工效)。

       

      Abstract: Thin coal seam mining is an important issue for the coal mining in China, thin coal seam mining method selection become more and more important. The geological conditions, management and equipment decide to the optimization selection of thin coal seam mining method base on the characteristics of thin coal seam mining, an optimization selection expert system(ES) of thin coal seam mining method based on neural networks (NN) is built. This system uses the self-adaptation algorithm to train the network. Finally, the mining method, yield and work efficiency can be predicted by this system.

       

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