Study of BP Network for a Cylinder Shells Support identification

摘要：

Some key technologies of neural network for structural damage identification, such as structural design of BP network, input parameter forms, training methods, learning rules and so on, are discussed. Modal parameters of a cylindrical shell structure under different support conditions are tested. Then these data are used as training samples for BP network, and depending on whether using random error, two different BP network is trained. Performance of these trained BP network in different case of test error is studied. The results show that adding a random error to the training samples can effectively improve the recognition ability of a BP network.

关键词： BP neural network cylindrical shell structure support conditions random noise

作者: Luo Yaozhi Tong Ruofei

作者单位: Department of Civil Engineering, Zhejiang University, Hangzhou, 310058, China

会议类型: 国际会议

会议名称: The 4th International Conference on Technology of Architecture and Structure Xian 2011(2011中国(西安)国际建筑科技大会)

会议地点: 西安

会议语种:英文

页码: 447-453

在线出版日期: 2011-09-22（万方平台首次上网日期，不代表论文的发表时间）