地下金属矿山岩层移动角选取的进化支持向量机模型及工程应用  被引量:14

Nonlinear SVM with GA in determination of the motion angle of terrane in underground metal mine and its application in engineering

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作  者:高栗[1,2] 李夕兵[1] 张楚璇 

机构地区:[1]中南大资源与安全工程学院,湖南长沙410083 [2]长沙环境保护职业技术学院,湖南长沙410004

出  处:《采矿与安全工程学报》2014年第5期795-802,共8页Journal of Mining & Safety Engineering

基  金:国家重点基础研究发展计划(973)项目(2010CB732004);国家自然科学基金重点项目(50934006)

摘  要:为克服传统方法确定地下金属矿山岩层移动参数的缺点,提出基于支持向量机(SVM)理论的地采岩层移动角选取方法。选取影响岩层移动的7个主要因素(矿体上、下盘围岩普氏系数、稳固程度,以及开采深度、开采厚度、矿体倾角)作为模型的输入,上、下盘岩层移动角为模型的输出,在收集65组金属矿山开采岩层移动参数的基础上,根据不同开采技术条件,利用SVM强有力的模式识别功能,采用RBF核函数,分别建立了崩落开采和充填回采的岩层移动参数预计模型。为提高预测模型的泛化能力和预测精度,应用遗传算法选择SVM的模型参数。应用该模型预测了三山岛金矿和狮子山铜矿开采岩层移动参数。结果表明:模型选取的因素合理,建立的遗传算法优化SVM回归模型对地采岩层移动角预测效果良好,为岩层移动角评价提供一种新思路。In order to overcome the shortcomings of traditional methods to determine the parameter of terrane movement in underground metal mines, a new method of the support vector machine (SVM) to predict the motion angle of terrane (MAT) has been proposed. The main factors such as Pu’s coefficient of the hanging wall and foot wall of ore body, geologic conformation, mining depth, mining thickness and deposit angle have been selected as the input variables for the proposed model, and the MAT of hanging wall and foot wall as the output value for the proposed model. On the basis of the different mining conditions and 65 typical metal mines cases, the MAT prediction model of caving method and cut&filling method have been established respectively by using the powerful pattern recognition func-tion of SVM with radial basis function (RBF) kernel. In order to improve the generalization perfor-mance and prediction accuracy, genetic algorithm (GA) has been adopted to choose the parameters for SVM model in the current study, thus the MAT with GA-SVM re-gression model for caving method and cut&filling method is established, and Sanshandao gold mine and Sizishan copper mine cases are to be validated for further study of the effectiveness and practicality of the proposed model. The results show that the establishment of SVM regression model prediction of the MAT in underground metal mine can achieve a high accuracy, which provides a new approach to evaluation of the MAT and can be applied to practical engineering, which provides a new approach to evaluation of the MAT.

关 键 词:地下金属矿山 岩层移动角 支持向量机 遗传算法 预测 

分 类 号:TD325[矿业工程—矿井建设]

 

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