Research on Optimal Arrangement of Monitoring Sensors for High-piled Wharf Structure Based on Extreme Learning Machine
The whole life cycle monitoring of high-piled wharf structure is a huge system engineering,and the optimal arrangement of monitoring points is particularly critical.The ELM neural network model is established by finite element calculation,and the hyperparameters of ELM model are determined by K-flod method.The importance of monitoring points in the judgment of wharf state is evaluated by SBS strategy under Filter framework.The global optimal search strategy in Wrapper method is used to give the optimal layout scheme under selected monitoring points.The results show that the importance evaluation of the monitoring points of the wharf state prediction is similar to the global optimization results.This method can optimize the layout of the monitoring points of the high-pile wharf structure.
万方数据
维普
