文章基本信息

标题：Prediction of Long-Term Seawall Settlement Based on Least Squares Support Vector Machine
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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.