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现代矿业 ›› 2011, Vol. 27 ›› Issue (07): 10-12.

• 采选工程 • 上一篇    下一篇

BP神经网络在开采沉陷相似材料配比中的应用

王明柱1,2,3,郭广礼1,2,3,查剑锋1,2,3,王磊1,2,王强1,2,3   

  1. 1.中国矿业大学环境与测绘学院;2.江苏省资源环境信息工程重点实验室; 3.国土环境与灾害监测国家测绘局重点实验室
  • 出版日期:2011-07-13 发布日期:2011-07-14
  • 基金资助:

    国家自然科学基金重点项目(编号:50834004),中国矿业大学青年科研基金项目(编号:09091252),国土环境与灾害监测国家测绘局重点实验室开放基金项目(编号:LEDM2009B01)。

Application of BP Neural Network in the Proportion of Similar Materials of Mining Subsidence

Wang Mingzhu1,2,3,Guo Guangli1,2,3,Zha Jianfeng1,2,3,Wang Lei1,2,Wang Qiang1,2,3   

  1. 1.School of Environment Science and Spatial Informatics,China University of Mining and Technology;2.Jiangsu Key Laboratory of Resources and Environmental Information Engineering;3.Key Laboratory for Land Environment and Disaster Monitoring of SBSM
  • Online:2011-07-13 Published:2011-07-14

摘要: 相似材料模型试验是矿山开采沉陷机理研究的重要研究方法,相似材料配比是实现相似材料模型模拟可靠性的关键因素。由传统试验方法确定相似材料配比费时、费力。综合分析了相似材料选择原则,以中国矿业大学研究制作的相似材料配比表为基础,建立了相似材料配比的BP神经网络模型。以33组试验数据作为训练和测试样本,模型预测的最大相对误差为7.39%。研究表明:所建立BP神经网络模型可基本反映出相似材料抗压、抗拉强度与各材料配比之间的内在影响规律,用该模型进行相似材料配比预测是可行的。

关键词: BP神经网络, 开采沉陷, 模型试验, 相似材料, 配比

Abstract: The similar material model test is one important research method to study the mining subsidence mechanism,and similar material proportion is the key factor to achieve a reliable similar material model.Similar material proportion confirmed by traditional test method is time-consuming and laborious.A BP neural network model for similar material proportion was established based on the table of similar material proportion.33 groups of experimental data were used as training and testing samples,and the maximum relative error of model prediction was 7.39%.The result shows that the BP neural network model can basically reflect the inner influence rules between similar materials' compression and tensile strength and their proportion.It is feasible to predict the similar materials proportion by this model.

Key words: BP neural network, Mining subsidence, Model test, Similar material, Proportion