摘要
为了预测多因素影响下的铣削型钢纤维混凝土劈裂抗拉强度,建立了支持向量回归(SVR)预测模型。模型以铣削型钢纤维混凝土的钢纤维体积分数(φf)、粗骨料最大粒径(dmax)和水灰比(mW/mC)等参数为输入变量,以铣削型钢纤维混凝土劈裂抗拉强度(fft)为输出变量进行建模和预测。预测结果表明:SVR的预测模型具有较高的预测精度,能为铣削型钢纤维混凝土的配制提供参考。
In order to predict the splitting tensile strength of mill-cut steel fiber reinforced concrete(SFRC),a support vector regres⁃sion(SVR)model was established.For the model,the steel fiber volume fraction(φf),the maximum coarse aggregate size(dmax)and the water-cement ratio(mW/mC)of mill-cut SFRC as input variables act as input parameters,and the splitting tensile strength(fft)of mill-cut SFRC as output variables for modeling and prediction.The prediction results show that the prediction model of SVR has high prediction accuracy and can provide reference for the preparation of mill-cut steel fiber reinforced concrete.
作者
唐江凌
TANG Jiang-ling(Guilin Normal College,Department of physics and Engineering Technology,Guilin 541199,China)
出处
《电脑知识与技术》
2020年第19期226-227,共2页
Computer Knowledge and Technology
基金
2018年广西高校中青年教师基础能力提升项目“支持向量回归技术在混凝土强度预测中的应用研究”(项目编号:2018KY0916)。
关键词
支持向量回归
钢纤维体积分数
粗骨料最大粒径
水灰比
混凝土
support vector regression
steel fiber volume fraction
maximum coarse aggregate size
water-cement ratio
concrete