摘要
结合试验采集的回弹值和抗压强度值数据,基于粒子群(PSO)优化支持向量机(SVM)预测模型建立了南水北调工程河北段混凝土的专用回弹测强曲线。通过与传统的幂函数回归模型及BP神经网络模型作比较,证明PSOSVM预测模型具有较高的计算精度和较快的运行速度。研究成果为南水北调工程河北段混凝土回弹检测提供了理论依据和参考标准。
By using the rebound and compressive strength data of concrete experiment,the special rebound and strength curve is achieved for South-to-North Water Diversion Project in Hebei Province.The PSO-SVM prediction model has higher accuracy and faster running speed compared with the traditional exponential function and BP neural networks.The result provides a strong theoretical basis and reference standard for South-to-North Water Diversion Project in Hebei Province.
出处
《中国农村水利水电》
北大核心
2015年第3期135-138,共4页
China Rural Water and Hydropower
关键词
南水北调
混凝土
支持向量机
粒子群优化算法
回弹测强曲线
South-to-North Water Diversion
concrete
support vector machine
particle swarm optimization algorithm
rebound concrete strength