| 基于神经网络的采场底板分类与顶板来压预报 |
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| 引用本文： | 吴洪词. 基于神经网络的采场底板分类与顶板来压预报[J]. 贵州工业大学学报(自然科学版), 1996, 0(4) |
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| 作者姓名： | 吴洪词 |
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| 作者单位： | 贵州工学院采矿系 |
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| 摘 要： | 建立了长壁工作面底板分类及单体液压支柱底座选型的人工神经网络（ＢＰ网络）模型，并通过网络自适应学习与匹配联想，得出了采场底板类别与单体液压支柱底座型式相对应的结果。同时，通过邻城相互作用算法与ＢＰ网络耦合，预报了采煤工作面顶板来压。网络试验表明，所得结果与实际吻合良好。
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| 关 键 词： | 人工神经网络，采场，底板分类，自适应学习，邻域相互作用 |
FLOOR CLASSIFICATION AND ROOF WEIGHTING PREDICTION IN LONGWALL STOPE BASED ON NEURAL NETWORKS |
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| Wu Hongci. FLOOR CLASSIFICATION AND ROOF WEIGHTING PREDICTION IN LONGWALL STOPE BASED ON NEURAL NETWORKS[J]. Journal of Guizhou University of Technology(Natural Science Edition), 1996, 0(4) |
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| Authors: | Wu Hongci |
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| Abstract: | Artificial neural network methods are applied to two distinct aspects of the strata control in coal mine. The first aspect is the floor classification and prop base selection by means of adaptive learning and associating in BP (Back Propagation) algorithm. The second aspect is the prediction of the likely future weighting of main roof through hybrid algorithms of the neighbourhood interaction operation and the neural networks. And the network outputs are in a close agreement with the measured data. |
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| Keywords: | artificial neural networks longwall stope floor classification adaptive learning neighbourhood interaction main roof weighting prediction |
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