Dam deformation forecast model based on hierarchical diagonal neural network
Yang Yang · Engineering Journal of Wuhan University · 2009
In order to deal with dam monitoring data more effectively,a new deformation monitoring model has been proposed based on hierarchical diagonal neural network(HDHH) that can approximate any nonlinear function.The model takes water pressure,temperature and time factors as the input and dam displacement as the output.And then the series-parallel model identifier and dynamic BP learning algorithm play an important role in modeling.The dam deformation data fitting analysis and forecasting research show that the HDNN model is not only convergent quickly enough to improve the efficiency of the algorithm,but also has a good effect in fitting with monitoring data,which improves forecast accuracy a lot.In a word,HDNN has great validity and superiority in the dam safety forecast analysis.