采矿方法结构参数神经网络优化识别的应用  

Application of Artificial Neural Network in Optimization of Mining Structure Parameters

作　　者：苏家红[1] 

机构地区：[1]中南大学,湖南长沙410083

出　　处：《矿业研究与开发》2002年第4期27-29,共3页Mining Research and Development

摘　　要：叙述了应用神经网络进行采矿方法结构参数优化识别的原理和方法 ,并介绍了高峰矿的开采技术条件。选择矿体厚度、倾角、矿岩稳固性及采场布置方式作为输入量 ,选择矿房和矿柱的尺寸和分层高度作为输出量 ,构造了 3层结构的神经网络 ,用 2 4个采矿方法实例作为训练样本 ,然后用 6个实例验证。应用实例验证了该方法的可行性和实用性。The paper gives a detailed description of the principle and method of artificial neural network in the optimization of mining structure parameters. The mining technological conditions of the Gaofeng Mine are described. The selected input parameters include the thickness and dip angle of the orebody, the stability of rockmass and the layout of stopes. The selected output parameters include the dimensions of rooms and pillars and the height of sublevels. Therefore, a three-layer structured artificial neural network is created. 24 cases of mining methods are used as training samples and six practical cases are used for validation, which verify the feasibility and applicability of the method.

关 键 词：神经网络 采矿方法 结构参数 矿房 矿柱 稳固性 采场 

分 类 号：TD80[矿业工程—矿山开采] TP183[自动化与计算机技术—控制理论与控制工程]