Roadway displacement back analysis based on BP neural network optimized by particle swarm

Combined with the example of a coal mine,parameter level of physical and mechanical of rock mass in parameter selection scope was obtained,designed orthogonal test table on this basis.Geometric model was based on roadway boundary conditions,then got the displacement to establish PSO-BP neural network relevant study sample through finite element method,back analysis of displacement for prediction on rock physical and mechanical parameters model was obtained.The calculated result shows that the maximum error between the measured value and calculated displacement value by forecasting parameters is 3.27%.It is credible that physical and mechanical rock parameters can be obtained by means of inverse seeking displacement,so it appears that the PSO-BP network is feasible in mine roadway displacement back analysis.