Abstract
It is very difficult to obtain an accurate finite element method (FEM) model to further analyze structural mechanical properties. Therefore, as the main means of establishing accurate models, the model update has become a research hotspot in the dominion of bridge engineering. Particle swarm optimization (PSO) has the characteristics of being easy to implement, but it is easy to fall into the local optimum. Therefore, multistrategy cooperation particle swarm optimization (MCPSO) that balances exploration and exploitation of particle swarm is proposed. This algorithm achieves the goal of balancing exploration and exploitation by adopting different combinations of particle swarm velocity update strategies in different iteration stages. The application effects of MCPSO in the FEM model update of the continuous Warren truss steel railway bridge are compared and analyzed, and the results show that the algorithm proposed in this paper outperforms the standard PSO (SPSO) algorithm. This paper provides a more effective algorithm for bridge model updates.
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