Dam deformation monitoring model based on neural network with ant colony optimization algorithm

摘要：

Back propagation algorithm (BP) is widely used as a multilayer feedforward neural network model in the analysis of water engineering projects monitoring data, but it has low solution accuracy, slow search speed and easy to get into a local minimum. To overcome these shortcomings, in this paper, a new learning method of neural network with ant colony optimization (ACO) is introduced to achieve optimization solution of the model weights, the ACO-BP monitoring model of dam deformation is established as well. And actual examples show that the ant colony algorithm is effective and rapid.

关键词： ant colony optimization algorithm neural network deformation monitoring

作者: WEI Bo-wen XU Zhen-kai LIU He-zhi

作者单位: College of Civil Engineering and Architecture, Nanchang University, Nanchang 330031,P.R.China Colleg College of Civil Engineering and Architecture, Nanchang University,Nanchang 330031,P.R.China College of Water-conservancy and Hydropower, Hohai University, Nanjing 210098, China

会议类型: 国际会议

会议名称: 4th International Conference on Measuring Technology and Mechatronics Automation(第四届检测技术与机电自动化国际会议 ICMTMA 2012)

会议地点: 三亚

会议语种:英文

页码: 101-104

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）