Prediction of seawall foundation settlement based on the improved variable dimension fraction and artificial neural network model

摘要：

Prediction of the seawall foundation settlement it important to the engineering maintenance and disaster prevention. A new method based on the improved variable dimension fraction (IVDF) and artificial neural network (ANN) was presented on the example of the seawall located in Zhejiang Province of China. The settlement displacement analysis for a single point located on the seawall was performed. The analysis consists of three stages: idea of IVDF — ANN model analysis, IVDF-ANN modeling, and deformation forecast. The resnlt proves that IVDF-ANN model makes good use of the self-similarity of fractal theory and the self-learning ability of artificial neural network, and the method has a degree of applicability.

关键词： improved variable dimension fractal artificial neural network seawall settlement prediction

作者: Qin Peng Qin Zhihai

作者单位: Department of Hydraulic Engineering Zhejiang Water Conservancy and Hydropower College Hangzhou China Department of Civil Engineering Zhejiang Water Conservancy and Hydropower College Hangzhou China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 347-350

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）