软岩工程支护的双层SVM的智能设计方法  

Intelligent design method for soft rock engineering supporting based on tow layer support vector machines

作　　者：滕文彦[1] 乔春生[1] 胡宇庭[2] 

机构地区：[1]北京交通大学土木建筑工程学院,北京100044 [2]石家庄铁路职业技术学院土木工程系,石家庄050041

出　　处：《北京科技大学学报》2005年第4期395-398,共4页Journal of University of Science and Technology Beijing

基　　金：国家自然科学基金资助项目(No.50078002)中国铁道建筑总公司科技研究开发资助项目(No.G02-10A)

摘　　要：将一种机器学习算法——支持向量机引入到软岩工程支护设计领域,并根据问题需要提出了一种支持向量机回归算法且编制了相应的计算程序.工程算例证明,这种算法在学习样本数量很少的情况下就可以得到很高的预测精度,且具有推广性能好的优点,避免了人工神经元由于存在过学习问题而带来的网络参数难以确定的弊病,为类似工程的支护设计提供了一种新的途径.A machine learning algorithm--Support Vector Machines （SVM） was introduced into the field of soft rock engineering supporting design. An improved Support Vector Machines Regression （SVR） algorithm was presented to meet the needs of this problem and the corresponding calculation code was programmed, It is concluded that a high degree of prediction accuracy and a very good generalization can be obtained with small quantity of learning samples using this algorithm from the calculated results of an engineering instance. It can avoid the overfitting problem of artificial neural network （ANN） which brings the difficulty in determining the parameters of ANN. It facilitates users to a great extent and provides a new way in the supporting design of similar engineering.

关 键 词：软岩工程 支护设计 支持向量机 机器学习 回归预测 

分 类 号：TD350.1[矿业工程—矿井建设] TP391.4[自动化与计算机技术—计算机应用技术]