首页    期刊浏览 2024年07月08日 星期一
登录注册

文章基本信息

  • 标题:Prediction of Long-Term Seawall Settlement Based on Least Squares Support Vector Machine
  • 本地全文:下载
  • 作者:Guo-chang Ge ; Fang-yi Jin
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2018
  • 卷号:153
  • 期号:6
  • 页码:062036
  • DOI:10.1088/1755-1315/153/6/062036
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要:In this study, the basic principle of the least squares support vector machine (LS- SVM) method was introduced systematically. The method was applied in a seawall engineering project to establish a prediction model of long-term seawall settlement based on the LS-SVM method, and the model parameters were optimized based on the genetic algorithm. Based on the monitoring data of seawall settlement during the construction of a soft foundation seawall project in Wenzhou, China, a sample was selected to train the model, and the predicted value of long-term settlement calculated by the model was compared with the measured sample value. The results show that, with highly accurate and reliable prediction results, the prediction model of long-term seawall settlement based on the LS-SVM method possesses great application value.
国家哲学社会科学文献中心版权所有