Displacement prediction of open-pit mine slope based on SSA-ELM

Mine geological disaster is a complex non-linear system. The traditional prediction model has the disadvantages of low accuracy and poor reliability. In order to solve this problem, open-pit mine slope displacement taken as research object. Based on new algorithm extreme learning machine (ELM), intelligent sparrow search (SSA) are introduced determine weights thresholds input layer hidden ELM. improved ELM constructed applied an engineering example. results show that root mean square error SSA-ELM only quarter BP model, which 50% higher than GM (1,1) models. correlation coefficient 0.983, better model. single PSO-ELM SSA improvement effect. good comprehensive performance high accuracy. It feasible apply it in mines.