郑州大学学报（理学版）Issue(3)：59-63,5.DOI:10.3969/j.issn.1671-6841.2015.03.011
基于灰色关联支持向量机的混凝土抗压强度预测
Prediction of Concrete Compressive Strength Based on Grey Relational-support Vector Machine
摘要
Abstract
The prediction of concrete compressive strength was dynamic system engineering, and its accu-racy was affected by a variety of high dimensional nonlinear, random factors. To effectively improve the prediction accuracy of concrete compressive strength, a prediction model of concrete compressive strength based on grey relational-support vector machine ( GR-SVM) was constructed on the basis of the analysis of support vector machine ( SVM) . The model based on grey relational analysis identified the main factors affecting the compressive strength of concrete, and established the nonlinear mapping relationship be-tween compressive strength and variables through the SVM. The grid search algorithm was used to opti-mize the parameters of SVM. Simulation results showed that compared with single SVM and BP ANN, the prediction results based on GR-SVM forecasting model was more effective and reliable, and a new way would be introduced to improve the prediction accuracy of concrete compressive strength.关键词
混凝土/灰色关联分析/支持向量机/预测Key words
concrete/grey relational analysis/support vector machine ( SVM)/prediction分类
建筑与水利引用本文复制引用
靳江伟,董春芳,冯国红..基于灰色关联支持向量机的混凝土抗压强度预测[J].郑州大学学报（理学版）,2015,(3):59-63,5.基金项目
黑龙江省青年科学基金项目,编号QC2014C010 （）
