Research on the mining roadway displacement forecasting based on support vector machine theory

Abstract

In view of the difficulty in supporting the surrounding rocks of roadway 3–411 of Fucun Coal Mine of Zaozhuang Mining Group, a deformation forecasting model was put forward based on particle swarm optimization. The kernel function and model parameters were optimized using particle swarm optimization. It is shown that the forecast result is very close to the real monitoring data. Furthermore, the PSO-SVM (Particle Swarm Optimization-Support Vector Machine) model is compared with the GM(1,1) model and L-M BP network model. The results show that PSO-SVM method is better in the aspect of prediction accuracy and the PSO-SVM roadway deformation pre-diction model is feasible for the large deformation prediction of coal mine roadway.