肖云华,王清,陈剑平,张鹏,阙金声
XIAO Yun-hua1,WANG Qing1,CHEN Jian-ping1,ZHANG Peng1,QUE Jin-sheng2(1.Constructioin Engineering College

• 1:吉林大学建设工程学院
• 2:北京国电华北电力工程有限公司

摘要(Abstract)：

从数据融合角度出发,把粗糙集理论和支持向量机理论结合,用来解决隧道岩体质量评价问题。首先,应用粗糙集理论对岩体质量评价样本数据进行约简,去除冗余特征形成岩体质量影响因素与岩体质量之间简明扼要的关系数据表达形式,形成新的样本数据,然后应用支持向量机理论,对新样本数据进行学习,建立岩体质量的支持向量机评价模型。通过实际工程应用表明,该方法科学可行。
Based on data fusion the method which combines the rough sets theory and the support vector machine theory is applied in assessment of engineering quality of rock mass.Firstly,applying the rough sets theory the sample data is reduced.Removing the redundant characteristics,the concise expression can be formed expressing the relation of the factors and the engineering quality of rock mass,and new sample data be formed.Then applying the support vector machine study the new sample data to establish the support vector machine evaluation model.Through application in the example,it indicates that the model is scientific and practical,and support vector ma-chine is a feasible method in the evaluation of tunnel rock quality.

关键词(KeyWords)： 数据融合;粗糙集;支持向量机;岩体质量
data fusion;rough sets;support sector machine;engineering quality of rock mass

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(40472136);; 教育部归国人员启动基金项目(120413133);; 吉林大学“985”计划项目(105213200500007)

作者(Author): 肖云华,王清,陈剑平,张鹏,阙金声
XIAO Yun-hua1,WANG Qing1,CHEN Jian-ping1,ZHANG Peng1,QUE Jin-sheng2(1.Constructioin Engineering College

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