Optimization Analysis of the Joint Structure in Steel Truss Bridge Based on GA-BP Neural Network
In order to overcome the problem of large modeling workload and inability to effectively re-flect the local stress state of nodes in finite element analysis methods,a GA-BP neural network node structure optimization prediction model was established based on steel truss bridges.Five parameters,including N1 diaphragm thickness,N2 diaphragm thickness,node plate thickness,stiffener thick-ness,and stiffener height,were set up at seven levels.A total of 42 sets of sample data were collect-ed,with weights and thresholds determined,and the node structure was optimized and analyzed.The results indicate that the GA-BP neural network model can optimize the structural components of nodes,and the predicted maximum stress value of nodes is similar to the finite element analysis re-sults,which verifies the effectiveness of the proposed model.
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