Nonlinear Displacement Analysis Model for Tunnel Based on PSO-BP Algorithm

With the rapid development recently,the particle swarm optimization(PSO) has been widely used as a bionic global optimization algorithm.Compared with the genetic algorithm,it embodies the characteristics of easy programming and less parameters.Combined with the construction of Datian double-arch tunnel in Tonghuang highway,a novel BP neural network based on PSO algorithm which had been adopted to optimize the weight value of the network is introduced into analyzing monitoring data in this paper.The optimal BP model,with improvement of the generalization ability and the nonlinear mapping relationship between time and displacement is established applied into fitting and predicting tunnel monitoring data.The mean prediction relative error of crown subsidence compared with measured displacement is only 3.1% based on the PSO-BP algorithm,so it can serve as an assistant tool in information construction of tunnel and similar geotechnical work.