| 基于PSO与LSSVR的坝体顺流向位移预测 |
| |
| 引用本文： | 刘延婷.基于PSO与LSSVR的坝体顺流向位移预测[J].人天科学研究,2014(4):49-50. |
| |
| 作者姓名： | 刘延婷 |
| |
| 作者单位： | 湖南省国土资源信息中心,湖南长沙410007 |
| |
| 摘 要： | 顺流向位移是坝体形变监测中的重要指标。针对神经网络、支持向量机模型存在的局限性，提出基于粒子群优化与最小二乘支持向量回归的模型对顺流向位移进行预测。结合实地坝体数据，通过与神经网络、传统支持向量机等模型进行对比实验和分析，结果表明，该方法具有误差低、计算效率高等特点。
|
| 关 键 词： | 顺流向位移 粒子群优化 支持向量回归 变形监测 参数优化 |
Prediction Model of Dam Displacement Based on PSO and LSSVR |
| |
| Abstract: | Displacement along the flow is important for dam deformation monitoring .To solve problems on neural network and support vector machine an approach based on particle swarm optimization and least square support vector regression is presented .With experiments of measured data and comparisons among traditional methods ,the results showed that this approach is more precise and efficient . |
| |
| Keywords: | Displacement Along Flow Particle Swarm Optimization Support Vector Regression Deformation Monitoring Parameters Optimization |
| 本文献已被 维普 等数据库收录！ |
